THE VOCABULARY OF AVIATION RADIOTELEPHONY COMMUNICATION IN SIMULATOR EMERGENCIES AND THE CONTRADICTIONS IN AIR TRAFFIC CONTROLLER BELIEFS ABOUT LANGUAGE USE BY JENNIFER DRAYTON A thesis submitted to the Victoria University of Wellington in partial fulfilment of the requirements for the degree of Master of Arts Victoria University of Wellington 2021
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THE VOCABULARY OF AVIATION RADIOTELEPHONY COMMUNICATION IN SIMULATOR
EMERGENCIES AND THE CONTRADICTIONS IN AIR TRAFFIC CONTROLLER BELIEFS ABOUT
LANGUAGE USE
BY
JENNIFER DRAYTON
A thesis
submitted to the Victoria University of Wellington
in partial fulfilment of the requirements for the degree of
Master of Arts
Victoria University of Wellington
2021
ii
iii
Abstract
This thesis encompasses a mixed methods enquiry into the language used in air traffic
control in simulated emergency situations in the United Arab Emirates. The workplaces
studied employ pilots and controllers from a diverse range of language backgrounds. This
research sets out to answer three questions:
1. What is the technical vocabulary of aviation radiotelephony in emergency training in
the simulator?
2. To what extent is technical vocabulary used in radiotelephony in emergency training
in the simulator?
3. What factors influence the use of technical vocabulary in speaking?
The first part of the study investigates the nature of technical language in aviation
radiotelephony. Two spoken corpora were created from recordings of three air traffic
controllers from two different workplaces (Ghaf and Sandy aerodromes), undergoing
emergency simulator training. Mandated standard phraseology formed a written corpus.
Standard phraseology is an international language defined by the International Civil Aviation
Organisation (ICAO) and adopted by governments for use in radiotelephony communication.
Quantitative analysis showed that the technical vocabulary in aviation radiotelephony
consists of proper nouns, numbers, aviation alphabet, acronyms, technical word types and
multiword units. The technical word types included purely technical words e.g. taxiway and
cryptotechnical vocabulary (high, medium and low frequency words with a technical
meaning (Fraser, 2009)) e.g. approach. Multiword units included ICAO standard phraseology
e.g. hold short or subsidiary and local phraseology in the spoken corpora e.g. Do you have
any question (subsidiary) and engine start approved (local).
The second part of the study examines sources of difference in language use by controllers.
Technical vocabulary coverage differed between the spoken corpora at 70.52% for Ghaf
Aerodrome and 51.61% for Sandy Aerodrome. Two explanations for this were: differences
in the purpose of emergency training in each aerodrome; and differences in linguistic style
by the Sandy controller which was established through keyword analysis. Interviews with
nine controllers established further factors which are likely to affect the use of technical
iv
vocabulary in radiotelephony communication including: communication styles of native
English speakers (NES) and non-native English speakers (NNES).
Further examination of interview data also revealed contradictory beliefs underlying
language use by controllers. Their beliefs diverge around the role of standard phraseology,
its use (or not) in emergencies and the value of language training for emergencies. This
divergence reflects the contradictions in definitions of standard phraseology and plain
language in the literature. Differences in language use can lead to frequent
miscommunication and the need for clarification of meaning in these UAE workplaces.
The present study makes two contributions to the significant body of research on aviation
radiotelephony. The first is an Aviation Radiotelephony Word and Number List. It is used to
clarify the role of technical vocabulary and plain language in radiotelephony and to show
how the technical vocabulary coverage of radiotelephony communication, in an extract
from the simulator emergency training and another extract from an ICAO document, is high
compared to other professions. Second, a Model of Controller Beliefs and Outcomes is
presented and suggests a way to interpret divergent language outcomes in radiotelephony.
The model summarises two contradictory sets of controller beliefs about standard
phraseology, language in emergencies, and training. Further, the language and training
outcomes reflect those beliefs.
The investigation concludes with implications for training and testing in aviation for ab initio
and experienced controllers. The corpora, word and number list and model all provide
useful tools for the training and testing needs in these UAE workplaces. The chapter
concludes with limitations of the study and future research directions.
v
Acknowledgements
I would first like to extend my thanks to my supervisor Professor Averil Coxhead. It was such
a pleasure to work with you on this project. You expected me to work to my potential and
provided support so I could. For me, 2020 was a stressful year, but your sense of humour
and care meant a lot of laughs which helped make the difficult job of writing a thesis as
enjoyable as it could be. Both personally and professionally, I could not have asked for a
better thesis supervisor.
Second, to the participants, thank you for being so willing to help out and answer my
questions as completely and honestly as possible. I could not have completed this project
without you. My hope is that your contribution will help the aviation industry to progress in
some way. Along with the participants, I’d also like to thank my pseudo pilot colleagues for
problem-solving to make sure the recordings could happen and for being willing to be
recorded – Ryan, Yoken, Danish and Zair.
I would like to thank my previous employer GAL Air Navigation Services LLC where I worked
for six years, during which time I was lucky enough to work alongside, teach and learn from
numerous very accomplished Emirati and ex-pat personnel. To my ex-colleagues, thank you
for being part of my learning journey, for your professionalism and for going the extra mile
to answer my questions and help me do my job. There isn’t space here to name you all, so
I’ve limited names to those directly involved with the thesis or part of my immediate
workplace at the GAL ANS Training Centre. To Mike Barry and Jesse Guillen Jr, air traffic
control instructors with many years’ experience in the air traffic field, who willingly and
comprehensively answered my questions when we were in the workplace together and
since my arrival in New Zealand to complete this project, thank you. At the training centre, I
shared an office with Chris Carmody (a seasoned air traffic controller and instructor) for
more than two years, who approached all my questions with patience and comprehensive
answers. My former manager Kaj Christensen gave me the role of course developer and the
support I needed to fulfil my obligations, so that I played a significant role in developing
courses related to aviation safety and, along the way, learnt much of the knowledge that
underpins this thesis. My thanks to the training centre manager, Dennis Chavez, who gave
permission for me to interview controllers and record them in the simulator.
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To my friend and colleague Maria Treadaway who contributed useful insights for the
process of thesis writing and gentle humour.
I have benefitted from conferences and conversations with my International Civil Aviation
English Association (ICAEA) Research Group colleagues who have engaged in interesting and
helpful discussion about aviation English radiotelephony.
The knowledge required to write this thesis is the work of a village. To all those in my village
who have had a part in helping me in some way, large or small, I thank and salute you. I
could not have done this without your input.
Finally, to my friends and family who have waited patiently while I finish this endeavour,
thank you for your kindness, love and support.
vii
Contents
Abstract ............................................................................................................................ iii
Acknowledgements ........................................................................................................... v
Contents ...........................................................................................................................vii
Tables ................................................................................................................................ x
Figures ............................................................................................................................... x
Extracts .............................................................................................................................xi
Appendices ........................................................................................................................xi
Glossary of terms .............................................................................................................. xii
Chapter 1 Introduction .......................................................................................................... 1
1.1 Background - Emergency training in the simulator ....................................................... 1
1.2 Why this study? ........................................................................................................... 2
1.3 A change of direction ................................................................................................... 3
1.4 Aims of the study ......................................................................................................... 4
1.5 Overview of the thesis ................................................................................................. 5
Chapter 2 Literature review .................................................................................................. 7
2.1 What is the language of aviation radiotelephony? ....................................................... 7
2.1.1 Standard phraseology and subsidiary phraseology ................................................ 7
2.1.2 Plain language .................................................................................................... 11
2.1.3 How are standard phraseology and plain language combined? ........................... 13
2.1.4 Standard phraseology and plain language in emergencies .................................. 13
2.2 What does corpus analysis say about aviation radiotelephony? ................................. 14
2.2.1 What is technical vocabulary? ............................................................................. 16
2.2.2 Corpus analysis to examine technical vocabulary ................................................ 17
2.3 Factors that influence the use of technical vocabulary in aviation .............................. 19
2.4 Summary of literature review .................................................................................... 21
viii
Chapter 3 Methodology ...................................................................................................... 23
3.1 Background ................................................................................................................ 23
3.1.1 Participants ......................................................................................................... 23
3.1.2 Ethics .................................................................................................................. 25
3.2 Data collection ........................................................................................................... 25
3.2.1 Spoken corpus .................................................................................................... 25
3.2.2 Written corpus.................................................................................................... 26
3.2.3 Interviews ........................................................................................................... 28
3.3 Data analysis .............................................................................................................. 28
3.3.1 Adapting tools for aviation language ................................................................... 29
3.3.2 Tagging the corpora to retain proper nouns and numbers .................................. 30
3.3.3 Identifying technical vocabulary in aviation radiotelephony ............................... 32
3.3.4 Keyword analysis for language use...................................................................... 35
3.3.5 Interview analysis ............................................................................................... 36
3.4 Summary of methodology.......................................................................................... 36
Chapter 4 Results ................................................................................................................ 38
4.1 RQ: What is the technical vocabulary of aviation radiotelephony in emergency training
in the simulator? ............................................................................................................. 38
4.1.1 Proper nouns and semantic categories ............................................................... 41
4.1.2 Numbers and semantic categories ...................................................................... 41
4.1.3 Alphabet letters .................................................................................................. 42
4.1.4 Acronyms............................................................................................................ 43
4.1.5 Word types and semantic categories .................................................................. 43
4.1.6 Multiple Word Units: ICAO standard phraseology, subsidiary phraseology, and
local phraseology......................................................................................................... 44
ix
4.2 RQ: To what extent is technical vocabulary used in radiotelephony in emergency
training in the simulator? ................................................................................................ 46
4.3 RQ: What factors influence the use of technical vocabulary in speaking? .................. 47
4.3.1 The exercises and purpose of the simulator training sessions ............................. 48
4.3.2 Language choices controllers make ..................................................................... 50
4.3.3 Environmental factors that influence the use of technical vocabulary in the
workplace .................................................................................................................... 55
4.4 Summary of results .................................................................................................... 58
Chapter 5 Discussion ........................................................................................................... 59
5.1 Technical vocabulary coverage compared to other professions ................................. 59
5.2 Using the Aviation Radiotelephony Word and Number List to examine the role of plain
language .......................................................................................................................... 60
5.2.1 An emergency in the simulator ........................................................................... 61
5.2.2 An emergency involving a critically ill patient...................................................... 63
5.2.3 Plain language in aviation radiotelephony........................................................... 66
5.3 Miscommunication and controllers’ beliefs about standard phraseology ................... 67
5.4 Summary of discussion .............................................................................................. 71
Chapter 6 Conclusion .......................................................................................................... 73
6.1 Focus and contribution of this study .......................................................................... 73
6.2 Implications for training ............................................................................................. 74
6.3 Implications for testing .............................................................................................. 75
6.4 Limitations ................................................................................................................. 76
6.5 Future research ......................................................................................................... 77
6.6 Concluding remarks ................................................................................................... 78
References....................................................................................................................... 79
Appendices ...................................................................................................................... 86
x
Tables
2.1 The effect of removing vocabulary items on corpus size in study by Lopez, Condamines,
Josselin-Leray, et al. (2013) ................................................................................................. 16
2.2 Coverage of technical language in written and spoken corpora ..................................... 18
3.1 Research participants .................................................................................................... 24
3.2 Ghaf and Sandy Aerodrome spoken corpora emergencies............................................. 26
3.3 Chapters from ICAO and GCAA documents included in the written corpus .................... 27
3.4 Establishing tags for proper nouns and numbers for a single transmission in the written
corpus ................................................................................................................................. 32
3.5 Size of corpora for keyword analysis.............................................................................. 35
4.1 Technical and non-technical vocabulary in corpora ....................................................... 39
4.2 First 25 word and number types in the Aviation Radiotelephony Word and Number List
........................................................................................................................................... 40
4.3 Technical multiword units which occur > 10 times in the list ......................................... 45
4.4 Technical vocabulary coverage in the written and spoken corpora ................................ 47
4.5 Workplaces of controllers interviewed .......................................................................... 47
4.6 Use of plain language by the Sandy aerodrome controller ............................................. 51
4.7 Comparison of language used in the Sandy, Ghaf and written corpora .......................... 52
Figures
4.1 A selection of aircraft types belonging to the proper noun category aircraft type
(ACTYPE) ............................................................................................................................. 41
4.2 A selection of numbers represented by the number categories HDGNUMBER and
WINUMBER ......................................................................................................................... 42
4.3 Aviation alphabet letters represented by the tag AVALPHABET ..................................... 43
5.1 A Model of Controllers' Beliefs and Language/Training outcomes in aviation
radiotelephony.................................................................................................................... 68
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Extracts
2.1 Extract of a routine pilot controller exchange .................................................................. 8
5.1 Extract from Ghaf corpus: Engine flameout emergency ................................................. 62
5.2 Extract of a military pilot requesting diversion possibilities: Medical emergency ........... 64
Appendices
Appendix A ...................................................................................................................... 86
A.1 Information sheet for participants ............................................................................. 86
A.2 Consent to record training session and interview ...................................................... 88
A.3 Information sheet for GAL ANS training centre .......................................................... 89
A.4 Consent to record training sessions and interview trainees at GAL ANS training centre
........................................................................................................................................ 91
A.5 Protocol for recruitment of research participants ...................................................... 92
Appendix B Interview questions ...................................................................................... 94
Appendix C Tags for identification of technical vocabulary .............................................. 95
Appendix D Aviation Radiotelephony Technical Word and Number List ......................... 101
xii
Glossary of terms
Aviation Terms
Term Definition
ICAO Annex There are 19 ICAO annexes which contain the regulatory requirements for aviation (see SARPs below)
Approach controller
The approach controller uses radar to sequence aircraft for landing and departure. They hand aircraft over to the tower controller for landing and aircraft are passed from the tower controller to the approach controller once they have taken off
ICAO Document Documents identify how the SARPs in ICAO Annexes are to be implemented
GCAA General Civil Aviation Authority - the government body in the UAE which oversees all aviation activity and ensures compliance with regulations
Ground controller
A controller who is responsible for all aircraft and vehicle movements around the aerodrome, except for the runway
Holding point A threshold next to the runway at which an aircraft waits until the pilot is given permission to taxi onto the runway
ICAO International Civil Aviation Organisation
Local phraseology
a term used in this paper to mean multiword units that replace ICAO standard phraseology e.g. engine start approved replaced start-up approved
LPR Language Proficiency Requirements. This refers to the requirement by ICAO that all non-native English speakers (NNES) reach a minimum level of English language proficiency. This requirement was implemented in 2011 and NNES must prove their language ability to retain their license to practise as an air traffic controller or pilot
POB Persons on Board
Radiotelephony Communication between air traffic controllers and other personnel including, but not limited to, pilots, other air traffic controllers, emergency vehicle drivers, emergency services and engineering personnel which is conducted over the radio
SARPs Standards and Recommended Practises provided in ICAO regulatory Annexes
xiii
SOP Standard Operating Procedures - these are the rules that aviation personnel must follow in order to do their job. They are contained in manuals in each workplace
Standard phraseology
multiword units contained in ICAO Documents and mandated by governments to be used in air traffic control communication
Subsidiary phraseology
multiword unit(s) developed for a particular standard operating procedure(s), in an individual workplace or country which is not covered in the ICAO documents. Subsidiary phraseology is used in addition to standard phraseology
Taxi describes the movement of an aircraft from one part of an airport to another via taxiways. It means the same as drive for a car.
Tower controller
A controller who is responsible for all aircraft and vehicle movements onto and off the runway. They are responsible for clearing departing and landing traffic to take-off or land
UAE United Arab Emirates
Linguistic Terms
Term Definition
ESP English for specific purposes
MWU Multiword Unit: composed of two or more words and/or numbers
NES Native English Speaker
NNES Non-Native English Speaker
1
Chapter 1 Introduction
Aviation English has been the subject of numerous academic studies across a range of
topics. Arguments have been made for a broad definition of aviation English as an English
for Specific Purposes (ESP) which encompasses the language needs of a variety of aviation
personnel such as pilots, cargo handlers and maintenance staff (Cutting, 2012; Wang, 2007,
2008). Other studies examine teaching aviation English as an ESP (Roberts, 2018; Roberts &
Orr, 2020; Roberts et al., 2019). Studies about cognitive factors (Barshi & Farris, 2013; Farris
et al., 2008), effect of accents (Tiewtrakul & Fletcher, 2010), pronunciation (Kim &
Billington, 2018) and speech recognition (Delpech et al., 2018; Smidl et al., 2019) have
focussed on language use in aviation. Further research focuses on language testing and
proficiency requirements (Alderson, 2009, 2011; Huhta, 2009; Mathews, 2004; Mell, 2004a,
2004b; Read & Knoch, 2009; Shawcross, 2004). The current study focuses on vocabulary and
sources of miscommunication in multilingual environments in the radiotelephony language
used by air traffic controllers.
This research was conducted in the United Arab Emirates (UAE) to find out more about the
language used in simulator emergencies in air traffic control. Recordings were made of
emergency simulator training for two aerodromes (Ghaf and Sandy) at GAL ANS Training
Centre. Interviews were conducted with air traffic controllers from Ghaf, Sandy, Desert and
Dune aerodromes to learn about the sources of difference in language use in the workplace.
Pseudonyms have been used.
1.1 Background - Emergency training in the simulator
This study was conducted in an air traffic control simulator for two reasons. First,
emergency training is essential for air traffic controllers to retain their licence to work in the
UAE. The training is done in an air traffic control simulator for at least four hours per year
(GCAA, 2016). Second, I could not get permission to conduct this research in air traffic
control workplaces.
The simulator training consists of a series of exercises, each including one or more
emergencies and taking thirty to forty-five minutes. The simulator mirrors the controller’s
work environment as closely as possible. The controller sits at a workstation; uses a
headset; has flight strips to identify aircraft; and uses a phone line for coordination with
2
other controllers. The controller can see the airport as if they were in their workplace. They
talk to pilots and see aircraft respond just as they would on the job.
The focus of the emergency training is not usually language. However, controllers employed
by GAL ANS must be proficient in general English to Level 4 according to criteria set by the
International Civil Aviation Organisation (ICAO, 2018) since language proficiency equips
controllers and pilots to successfully resolve emergencies (ICAO, 2010). That said, since
aviation English is a safety critical aspect of emergencies, it is essential that the language of
all users is better understood in order to inform training and testing needs.
1.2 Why this study?
There are three reasons I wanted to do this research. First, I listened to a student with good
English stumble over the phrase startup and pushback approved in week 9 of her 12-week
air traffic controller course. She was corrected by the instructor. I felt that she should be
fluent in basic phrases by week 9, but the combination of air traffic control training and
language training together seemed to hamper her progress. Radiotelephony language
training outside the air traffic control simulator could help her fluency (Drayton & Kelly,
2019). Second, I had always understood that plain or possibly general English language was
needed in emergencies rather than standard phraseology. Standard phraseology is an
international language defined by the International Civil Aviation Organisation (ICAO) and
adopted by governments for use in radiotelephony communication. When I listened to
emergency training by experienced air traffic controllers, I heard standard phraseology. My
colleague explained that this was because emergencies can be resolved by experienced
personnel with standard phraseology. Another colleague told me about a civil airport
emergency with a tyre bursting on take-off. He described the incident as having been dealt
with smoothly and that the language used was ‘all phraseology’. Third, my colleagues stated
that non-native English speakers (NNES) were better at radiotelephony communication. To
help my students do better in the simulator, I wanted to know more about the language
used in emergencies.
At the time the data was gathered, I was a course developer for GAL ANS Training Centre,
writing courses for air traffic controllers that focussed on safety. Prior to that, I taught
English to students who would go on to train as air traffic controllers. I was interested in
3
preparing students for the challenges they would face in their training and wanted to know
more about the language they would be required to use. I was also interested in the
importance of language in radiotelephony communication to safety.
1.3 A change of direction
Initially, I wanted to know when or how standard phraseology and plain language are used
in emergencies. I thought their use would be clearly delineated in radiotelephony, however
it proved difficult to distinguish one from the other. Further, the International Civil Aviation
Organisation (ICAO) documents contained contradictions in the definitions of standard
phraseology and plain language. Models of how standard phraseology and plain language
are combined were useful but did not help me to make judgements about what to count as
standard phraseology or plain language. Any analysis which attempted to separate standard
phraseology and plain language would be subjective, difficult to carry out, and produce
questionable results. The difficulty encountered in trying to measure the extent to which
standard phraseology or plain language are used in aviation radiotelephony is best
demonstrated with the use of an example. The sentence below is an instruction from an air
traffic controller to a pilot taken from the recorded data in the current research project.
(1) You can ah taxi and exit at Delta. (2) Do you just want to hold on taxiway tango
then? (Sandy Aerodrome Corpus).
In the example above, it is clear that the words taxi, exit, delta, hold, taxiway and tango are
technical words in aviation radiotelephony. However, it is difficult to identify if they should
be counted as standard phraseology or as plain language. Neither sentence (1) nor (2)
matches sentences found in the ICAO Document 9432 Manual of Aviation Radiotelephony,
yet they are both highly technical. Should they be counted as plain language since plain
language is highly technical (Estival & Farris, 2016)? Or should exit at Delta in the first
sentence be counted as standard phraseology since it differs from Exit kilo (ICAO, 2007, p.
5.2) by one word, means the same, but exit kilo is used with a vehicle rather than an
aircraft? In the second sentence, the word hold is used to ask the aircraft if they wish to stop
on taxiway tango. In the radiotelephony document, hold is used with short (hold short) to
tell a pilot or vehicle to stop before the runway; it is used to tell an aircraft to stay within a
certain area in the air; and finally with position to tell an aircraft to stop where they are
4
(ICAO, 2007). The meaning in the sentence above is closest to hold position, but it has been
shortened to hold. Should this be counted as standard phraseology or plain language? This
example shows how impractical the division into standard phraseology and plain language is
in practice.
Consequently, I turned to an applied linguistics approach for identifying technical
vocabulary in texts. This approach produced an Aviation Radiotelephony Word and Number
List which I used to learn more about the nature of specialist language in aviation
radiotelephony and its coverage. The list helped clarify what technical vocabulary is used in
radiotelephony and how controllers use it. It also provided a way to analyse air traffic
control interactions to understand what was being communicated, how it was
communicated and why. The technical vocabulary analysis and information gained from
interviews provided a clear picture of training needs for ab initio and experienced
controllers. The analysis confirms that communication in aviation radiotelephony uses a
highly technical, coded language (Estival & Farris, 2016). It is beyond English for Specific
Purposes (ESP) since such a characterisation places the onus for learning the language on
non-native English speakers (NNES) (Douglas, 2014). The language of aviation
radiotelephony is highly complex and needs to be learnt by all users, including native English
speakers (NES) (Clark, 2017; Estival, 2016). Any language-based approach to teaching should
combine the skills of a language teaching professional with the highly specialised knowledge
and skills of an aviation specialist because of the safety critical nature of radiotelephony
communication.
1.4 Aims of the study
The study aims to establish the nature of technical vocabulary used in air traffic control
emergency simulator training and the extent to which it is used. It further examines the
factors which influence differing use of technical vocabulary by air traffic controllers. The
intention is to identify training and testing needs in a UAE air traffic service (ATS) provider.
To meet these aims, this research investigates three questions:
1. What is the technical vocabulary of aviation radiotelephony in emergency training in
the simulator?
5
2. To what extent is technical vocabulary used in radiotelephony in emergency training
in the simulator?
3. What factors influence the use of technical vocabulary in speaking?
1.5 Overview of the thesis
This introductory chapter has provided the background, motivation, change in research
direction and purpose of the research. It includes an overview of the thesis and the research
questions investigated.
Chapter 2 reviews plain language and standard phraseology which are the two main
components of aviation radiotelephony. They are not clearly defined by ICAO and there are
contradictions in the literature. Contradictions also exist around the language used to
resolve emergencies. The second part of the chapter explores corpus analyses of
radiotelephony. Next, it outlines the use of corpus analysis to identify technical vocabulary
and research language use. The chapter concludes with an exploration of research which
identifies the sources of difference in radiotelephony language use by aviation professionals
in multilingual environments.
Chapter 3 outlines the methodology of the study. The first section provides details of
participant recruitment, data collection and interview procedures. The preparation of the
corpora for quantitative analysis is described along with tagging procedures. Quantitative
corpus analysis to create a technical wordlist, establish coverage and a keyword analysis of
controllers’ speech is outlined. Qualitative analysis of interviews with nine controllers is
explained.
Chapter 4 first presents the quantitative findings of the study, responding to research
questions one and two. The findings include an Aviation Radiotelephony Word and Number
List, and identification of the technical vocabulary in aviation radiotelephony. Technical
vocabulary coverage is presented. The answers to question three are drawn from a
quantitative keyword analysis and interview data, highlighting reasons for variation in
controller language.
Chapter 5 compares the coverage of technical vocabulary in emergency simulator training to
other professions and shows that it is a highly technical language. Next, the Aviation
6
Radiotelephony Word and Number List is used to examine two language extracts to clarify
the purpose and nature of plain language in radiotelephony communication. The chapter
presents a Model of Controller Beliefs and Outcomes which reflects findings on standard
phraseology and plain language from this study. This model links controller beliefs to
divergent language use and training outcomes.
The final chapter summarises the key findings in this study. The implications of the Aviation
Radiotelephony Word and Number List and Model of Controller Beliefs and Outcomes for
training and testing are examined. The chapter concludes with limitations, suggestions for
future research, and concluding remarks.
7
Chapter 2 Literature review
This chapter examines the context in which this study takes place by reviewing literature
related to aviation radiotelephony and relevant vocabulary research. It highlights some of
the issues and contradictions in the field and identifies the gaps which led to the research
questions stated in Chapter 1. The chapter is divided into three parts. The first investigates
the elements of aviation radiotelephony language. The second examines corpus analysis to:
investigate language use in radiotelephony; and identify technical vocabulary. The third
explores relevant sources of miscommunication in aviation.
2.1 What is the language of aviation radiotelephony?
This section explains the components of aviation radiotelephony. First, it explores the
standard phraseology contained in civil aviation documents, then reviews academic
literature related to standard phraseology. Second, plain language is examined from a
regulatory perspective, followed by its description in academic research. A contradiction in
the literature around what constitutes plain language is identified. Models for how standard
phraseology and plain language are used in spoken radiotelephony are examined. Finally,
the contradictions inherent in the literature about the use of standard phraseology and
plain language in emergencies are explored. Note that, standard phraseology and ICAO
standard phraseology are used interchangeably as are the terms controller and air traffic
controller.
2.1.1 Standard phraseology and subsidiary phraseology
ICAO (2007) makes a series of points about standard phraseology. First, the standard
phraseology contained in ICAO and government documents is not exhaustive and should not
be considered as such (GCAA, 2018; ICAO, 2007, 2016b). Standard phraseologies may be
supplemented by additional subsidiary phraseologies. Standard phraseology and subsidiary
phraseology must be used by ground personnel as well as pilots and controllers. That is, any
aviation personnel, including vehicle drivers and emergency services, who speak to air traffic
controllers must use this mandated language. Finally, plain language can be subsidiary
phraseology.
The regulations for the use of standard phraseology are contained in a series of ICAO
manuals which are called Annexes or Documents. The first of these is “Annex 10
8
Aeronautical Telecommunications Volume II, Communication procedures including those
with [Procedures for Air Navigation Services] PANS status” (ICAO, 2016a). Air navigation
service is the provision of air traffic control to keep aircraft (and vehicles) safe on the ground
and in the air. Annex 10 identifies the standards and recommended practices (SARPs) to be
achieved by United Nations member states. With regard to standard phraseology, ICAO
states:
ICAO standardized phraseology shall be used in all situations for which it has been
specified. (ICAO, 2016a, p. 5.1 emphasis added).
The word shall establishes ICAO standard phraseology as mandatory in air traffic control
communication. Annex 10 provides the groundwork for two ICAO Documents (“Document
4444 Procedures for Air Navigation Services: Air Traffic Management” and “Document 9432
Manual of Radiotelephony”) which cover the procedures for standard phraseology and
provide examples of the language. These manuals are legally binding once they are
implemented by a government in a national document (ICAO, 2016b) as they are in the UAE
document: “Civil Aviation Advisory Publication (CAAP) 69 UAE Radiotelephony Standards”.
CAAP 69 references the three ICAO documents mentioned above (GCAA, 2018) and makes
standard phraseology a legal requirement in all air traffic control communication. It includes
examples of phrases which relate to specific standard operating procedures, such as the
example given in Extract 2.1.
Extract 2.1
2.1 Extract of a routine pilot controller exchange
Turn and Speaker Transmission
1 Pilot: GROUND PAKISTAN 222 REQUEST TAXI
2 Air Traffic Controller:
PAKISTAN 222 GIVE WAY TO BOEING 747 PASSING LEFT TO RIGHT TAXI TO HOLDING POINT RUNWAY 02
3 Pilot: HOLDING POINT RUNWAY 02 GIVING WAY TO BOEING 747 PAKISTAN 222
Extract from GCAA (2018, p. 38 capitals in original).
9
There are four points to note in this example. First, this exchange follows the dialogue
structure of a pilot initiated call which is: pilot call, air traffic control response / instruction,
pilot readback of instruction (Estival, 2016). Second, the pilot is asking for taxi instructions to
get to the runway in Turn 1. There are two parts to the request. Standard phraseology
prescribes how speakers will identify themselves and others (ICAO, 2007, 2010, 2016a,
2016b), so the pilot addresses the controller (ground) and identifies who is speaking using
the aircraft callsign (Pakistan 222). Then, the pilot requests taxi instructions. Third, the
controller responds (Turn 2) by instructing the aircraft to taxi to the holding point, a position
just before the entrance to a runway at which the aircraft must wait for permission to enter
the runway. The number 02 tells the pilot the direction of the runway for take-off, and
therefore which holding point to use. Finally, the pilot must give way to an aircraft (Boeing
747) before taxiing. Fourth, in Turn 3, the pilot reads back the instruction (known as a
readback) while the controller listens to ensure the readback is correct (Estival, 2016; Koble
& Roh, 2013) and the flight crew executes the manoeuvre (Barshi & Farris, 2013; Howard,
2008). Extract 2.1 is an example of the language to be used for the Standard Operating
Procedure (SOP) to taxi to the holding point for an aircraft which intends to take-off. Each
example of standard phraseology is related to an SOP in this way (Howard, 2008; Mitsutomi
& O'Brien, 2003). In each case, the order information is presented in a transmission follows
that prescribed by ICAO (Estival, 2016; ICAO, 2016b).
Subsidiary phraseology is a subset of standard phraseology. It is used for operating
procedures which are not covered in the ICAO documents, but are specific to a country or
an airport. Subsidiary phraseology supplements standard phraseology identified in
international and national documents, but must not replace it (ICAO, 2007). Just like
standard phraseology, subsidiary phraseology must be clear, concise and unambiguous
(ICAO, 2007, 2016a, 2016b). Subsidiary phraseology can include plain language phrases
(ICAO, 2007, p. 3.2). It is not possible to provide an example of subsidiary phraseology here
since it is not contained in any of the above documents but would be included in the
standard operating procedures manual for an air traffic control centre.
Standard phraseology provides brief and efficient communication but differs from the
English language on which it is based. The first difference is the grammar used. Standard
phraseology has restricted grammatical structures (Estival, 2016; Intemann, 2008; Moder,
10
2013). The continuous tense is used to describe an ongoing action e.g. holding position, the
future tense is rare and confirmation of a completed action is given in the passive voice e.g.
brakes released (Intemann, 2008). Standard phraseology lacks pronouns, articles and
determiners (Intemann, 2008; Lopez, Condamines, & Josselin-Leray, 2013). In Extract 2.1,
callsigns (ground, Pakistan 222) replace I and you; and the controller says give way to
Boeing 747 (a or the before Boeing is omitted). Further, standard phraseology uses
imperatives rather than full sentences or interrogatives (Intemann, 2008; Moder, 2013) such
as taxi to holding point and request taxi in Extract 2.1.
The second difference is in the vocabulary used. Standard phraseology consists of a number
of multiword units (MWUs) or collocations (Bratanić & Anić, 2010) which each have a single
precise meaning (Bieswanger, 2016; Lopez, Condamines, Josselin-Leray, et al., 2013). Extract
2.1 contains the MWUs: request taxi, give way to (giving way to), passing left to right, taxi
to, and holding point. These MWUs are commonly used in aviation and have one meaning.
Further, aviation radiotelephony consists of a limited specialised vocabulary set (Intemann,
2008; Moder, 2013). The words have been carefully chosen to avoid phonological similarity
e.g. climb is used as the antonym for descend (Intemann, 2008). Numbers and letters are
delivered in specific ways e.g. alpha for the letter A, and niner for nine, so that nine is not
confused with the number five over the radio (Estival, 2016; ICAO, 2007; Moder, 2013).
Finally, the pronunciation of radiotelephony communication typically lacks intonation,
rhythm and pauses (Estival & Molesworth, 2009). Trippe and Baese-Berk (2019) found that
the difference between the rhythm of aviation communication and standard American
English was as distinct as between two different languages such as British English and
French or Dutch and Italian. These structural and vocabulary elements of standard
phraseology make it more efficient than English for communication between air traffic
controllers and pilots over the radio in routine situations (Borowska, 2017; Kim & Elder,
2009; Lopez, Condamines, Josselin-Leray, et al., 2013; Ragan, 1997; Varantola, 1989).
Finally, standard phraseology can only be understood by experts (Borowska, 2017; Lopez,
Condamines, Josselin-Leray, et al., 2013; Trippe & Baese-Berk, 2019). It relies on shared
understanding which allows the interlocuters to minimize their linguistic and cognitive load
in carrying out tasks (Hüllen, 1981; Lopez, Condamines, & Josselin-Leray, 2013; Moder,
2013; Moder & Halleck, 2009). This shared understanding is captured in an example from
11
Bullock (2015) in which he discusses the phrase ‘ABC123, going around’ said by a pilot. This
short phrase tells the controller that the pilot is cancelling their landing; will fly over the
runway; and then inform the controller of their intentions. This short phrase is immediately
understood by the controller and no further information is required until the pilot identifies
their intentions. Not only does this phrase highlight the shared understanding by pilot and
controller, it also demonstrates how effective communication is clear, concise and
unambiguous. Further, the relationship of this phrase to the procedure of ‘going around’ is
also clear. Finally, the volume of information implied helps explain why radiotelephony
language cannot be understood by laypeople.
2.1.2 Plain language
The ICAO definitions regarding plain language appear contradictory and are confusing. One
set of ICAO documents identifies plain language in relation to standard phraseology (ICAO,
2007, 2016a, 2016b). Another ICAO document defines it from a general English perspective
(ICAO, 2010). In the first set of documents, no definition is given for plain language and its
role is ambiguous. Section 2.1.1 identified that plain language could be used as subsidiary
phraseology to provide standard phrases unique to a particular location which become part
of the local standard operating procedures. However, plain language is also used in a more
immediate sense when standard phraseology is insufficient. The ICAO documents related to
radiotelephony communication all contain a phrase similar to:
Only when standardized phraseology cannot serve an intended transmission,
plain language shall be used (ICAO, 2016a, p. 5.1 emphasis added).
In other words, plain language serves two purposes: as subsidiary phraseology; and as the
language to be used when there is no standard phraseology. In both cases, plain language
must be clear, concise and unambiguous in keeping with the requirements of standard
phraseology (ICAO, 2007, 2016b). In these documents, plain language appears to be based
on standard phraseology. However, it appears to be defined simultaneously as a possible
subset of standard phraseology (subsidiary phraseology) and as language which is broader
than standard phraseology.
12
Another definition for plain language bases it on natural English. In a separate ICAO
document, plain language is defined as ‘The spontaneous, creative and non-coded use of a
given natural language’ (ICAO, 2010, p. x emphasis added) which is qualified as being:
constrained by the functions and topics (aviation and non-aviation) that are required
by aeronautical radiotelephony communications, as well as by specific safety-critical
requirements for intelligibility, directness, appropriacy, non-ambiguity and concision
(ICAO, 2010, p. 3.5).
and qualifies this by saying that the term plain was chosen rather than general, common,
extended or natural since plain is used in other ICAO documents (ICAO, 2010, p. x). In the
same document, ICAO asserts: ‘There is simply no more suitable form of speech for human
interactions than natural languages’ (ICAO, 2010, p. 1.2), suggesting that the definition for
plain language is based on general English. This definition implies that plain language may
replace standard phraseology if confusion arises. Other authors also suggest that natural or
plain English replaces ICAO phraseology (see: Intemann (2008); Lopez, Condamines and
Josselin-Leray (2013)). Finally, ICAO states that the term plain language is not to be confused
with the plain language movement in the UK and USA which advocates plain language for
legal and medical purposes and is a simplified form of technical language (Estival & Farris,
2016; ICAO, 2010). How plain language is also a technical language is not defined in any of
the ICAO documents. However, plain language in aviation may still be highly technical and
understood only by the professionals who use it (Estival & Farris, 2016; Hüllen, 1981;
Varantola, 1989), just as standard phraseology is.
The literature is contradictory and vague about what constitutes plain language. Firstly, it is
not clear how it is simultaneously a technical language and natural English. If it is used as a
natural language which replaces standard phraseology, then plain language should be
comprehensible to laypeople, but it is not. Perhaps plain language is technical when it is
used as subsidiary phraseology in which case, it may not be plain language. While some
studies identify the inclusion of greetings, signoffs, politeness markers, and questions as
further examples of plain language (Intemann, 2008; Moder, 2013) used to maintain
cooperative relationships with controllers or pilots (Hansen-Schirra, 2013; Lopez,
Condamines, & Josselin-Leray, 2013; Moder, 2013), the overall nature of plain language
remains unclear.
13
2.1.3 How are standard phraseology and plain language combined?
Three models explain how plain language and standard phraseology intersect in aviation
radiotelephony. The first is a three tier division of standard phraseology, English for Specific
Purposes (ESP), and finally, English for general purposes in which standard phraseology is
represented by a rectangle at the centre around which plain language forms a larger
rectangle followed by general English (Bullock, 2015). This model suggests that standard
phraseology is at the centre and may be replaced by general English in certain
circumstances. However, Bullock’s description is more nuanced as he provides examples in
which all three elements may be contained in communication, or there are varying
combinations of standard phraseology and ESP, or ESP and general English. The second
model is by Mitsutomi and O'Brien (2003). Again, standard phraseology is the central
element with ESP and general English expanding out from that. However, Mitsutomi and
O'Brien (2003) seem to advocate for using general English when standard phraseology is
insufficient. Bieswanger (2016) presents a third model which identifies standard
phraseology and plain language as two registers in aviation radiotelephony. Plain language is
an aviation English register with its own lexical, grammatical and pronunciation features,
while standard phraseology is the other register. Both registers are interchangeable and
must be learned. In these models, which include different categories or registers of
language, there is no clear indication of what counts as standard phraseology or plain
language when the two are combined (Prado & Tosqui-Lucks, 2019).
2.1.4 Standard phraseology and plain language in emergencies
While there has been a great deal written about the contribution of language errors to
aviation accidents (see e.g. Campbell-Laird (2004); Cookson (2009); Domogala (1991); Estival
and Farris (2016); Estival and Molesworth (2009); Green (1991); Varantola (1989)), there has
been very little written about the language used in emergencies that are successfully
resolved. The literature appears to contain contradictions about whether standard
phraseology or plain language is used in emergencies. Some writers state that air traffic
communications often deviate from standard phraseology in emergency situations towards
a more conversational style (Campbell-Laird, 2004; Yan, 2007) or that more plain language is
used in emergencies and unusual situations (Bullock, 2017; ICAO, 2010; Moder, 2013; Prado
& Tosqui-Lucks, 2019) because standard phraseology is insufficient for these situations (Yan,
14
2007). Read and Knoch (2009) state that there is an assumption that more plain language is
used in emergencies. Conversely, other authors claim that standard phraseology is useful for
routine and emergency situations, but not one-off unpredictable (unusual) situations
(Mitsutomi & O'Brien, 2003; Varantola, 1989). Further, air traffic controllers are expected to
be silent during emergencies because the pilots are busy in the cockpit and should not be
disturbed (Emery, 2014; ICAO, 2007). Three language related causes are identified as the
causes of aviation accidents and incidents: not using correct standard phraseology; lack of
language proficiency; and the use of more than one language in the same airspace (ICAO,
2010). These three causes imply that both standard phraseology and plain language may be
important in emergencies. However, it is unclear from the literature if standard phraseology
or plain language or a mix of the two is used in emergencies which are successfully resolved.
2.2 What does corpus analysis say about aviation radiotelephony?
Corpus analysis of aviation radiotelephony language has been used in aviation for training
student air traffic controllers and pilots. Three studies are relevant to this research. In the
first, Sullivan and Girginer (2002) carried out a discourse analysis of nine hours of
transcribed recordings of air traffic controller – pilot conversations in an air traffic control
centre in Ataturk, Turkey. The recordings were supplemented with questionnaires from 25
controllers and 25 pilots; and interviews with 10 controllers and 10 pilots. The study noted
differences in the way numbers are said compared to ICAO regulations and the addition of
greetings and closings in the data, as well as exchanges conducted in Turkish. Controllers
and pilots stated they needed more practise in conversational English since they often need
to supplement standard phraseology with general English. The study was done because one
researcher was a teacher of ab initio pilots and controllers, so the corpus was used to
develop training materials for use in an ESP classroom. Sullivan and Girginer (2002) appear
to have retained standard phraseology and plain language in their corpus, but this is not
discussed in their paper.
A second corpus study by Prado and Tosqui-Lucks (2019) compiled examples of non-routine
situations for research purposes and classroom use. Their goal was to collect unusual
situations, so that they would have a database of plain language use. They collected
recordings from the ATC.net website dated from 2008 onwards. They retained the sound
files and also made transcriptions. They used an ICAO document to identify categories of
15
non-routine incidents and aimed to gather three recordings for each one. The final corpus
was of 12 hours of transcribed audio which resulted in 110 737 words, in a total of 130 texts
categorised into 31 occurrence types. They were unable to determine the language
background of many of their speakers, but tried to include recordings of non-native and
native English speakers since they wanted to investigate language use from an English as a
lingua franca perspective (see, for example, Estival and Farris (2016), Kim and Elder (2009)).
Each transcript began when a problem was first mentioned and finished when the problem
was solved or handed to another professional. Prado and Tosqui-Lucks (2019) used this
corpus to examine word frequency and are currently conducting research on the structure
and vocabulary areas of the ICAO language proficiency requirement (LPR) rating scale (which
can be found in ICAO (2018)) and plan to also use the corpus to investigate fluency and
interaction according to the proficiency scale. The authors have used the corpus to examine
how plain language is used in aviation radiotelephony with a focus on how this is
represented in the ICAO LPR rating scale (for information about the rating scale see, for
example: Farris (2016a, 2016b)). However, the paper itself is a description of the corpus and
its compilation, concluding with suggestions for how it could be used to enhance research of
aviation English rather than with findings about plain language use.
Finally, Lopez, Condamines, Josselin-Leray, et al. (2013) compared a spoken corpus to a
written corpus to better understand how spoken radiotelephony compares to the ICAO
standard phraseology. The written corpus was created from the French government civil
aviation radiotelephony document (similar to the GCAA document in Section 2.1.1) and the
ICAO Document 9432 Manual of Radiotelephony (discussed in Section 2.1.1) to capture both
national and international language requirements (Lopez, Condamines, & Josselin-Leray,
2013; Lopez, Condamines, Josselin-Leray, et al., 2013). This written corpus established the
‘prescribed norm’ for air traffic controller – pilot interactions. The spoken corpus was
created from 22 hours of recordings of pilot - air traffic controller communication, recorded
in an air traffic control tower and two area control facilities. Before examining the data,
speech disfluencies, non-English politeness and greeting markers, proper nouns, aviation
alphabet letters, hapaxes (words that appear once), and numbers were removed (Lopez,
Condamines, & Josselin-Leray, 2013; Lopez, Condamines, Josselin-Leray, et al., 2013). The
study established lexical differences between spoken and prescribed language in the
16
corpora. The differences were in the use of nouns, adjectives, interjections, determiners and
pronouns (Lopez, Condamines, Josselin-Leray, et al., 2013). In a separate paper, Lopez,
Condamines and Josselin-Leray (2013) further identified that the word can was used by
controllers to politely convey authority in instructions such as you can fly heading 3-2-5. The
authors suggest that the corpus can be used to provide examples of language use in the
classroom and that the differences between the written and spoken corpus can be used to
highlight language use such as the use of can or may by aviation professionals.
The study by Lopez, Condamines, Josselin-Leray, et al. (2013) could be strengthened by
retaining all the data. The removal of items from the corpora including proper nouns, letters
and numbers substantially reduced the size of the corpora as Table 2.1 shows.
Table 2.1
2.1 The effect of removing vocabulary items on corpus size in study by Lopez, Condamines, Josselin-Leray, et al. (2013)
Written corpus
(initial size) Final size Reduction
Spoken corpus
(initial size) Final size Reduction
Types 805 566 29% 1,238 408 67%
Table data from Lopez, Condamines, Josselin-Leray, et al. (2013).
The table gives the number of word types before and after the removal of items e.g. the
number of types in the written corpus was 805 before removal and 566 afterwards, a
reduction of 29%. The word types in the spoken corpora were reduced by 67%.
Consequently, conclusions about standard phraseology and plain language are drawn from
33% of the data in the spoken corpus (Lopez, Condamines, Josselin-Leray, et al., 2013). It is
possible that retaining all items in the corpora would have provided information about the
amount and nature of technical vocabulary in each text which may allow for a richer analysis
of language use.
2.2.1 What is technical vocabulary?
This section examines the characteristics of technical vocabulary. A definition is provided by
Coxhead (2017):
17
Technical vocabulary would generally be expected to be limited in range to its
specialised subject area or discipline and to be well known and regularly used by
professionals in that field. People outside the specialised field might have a
limited knowledge of that vocabulary, or might have never heard or come across
these technical items at all. In some cases, the meaning of a word might be
vaguely known by laypeople, but a specialist would be expected to know much
more precise information about its meaning, use and nuances (p. 22).
There are a number of common elements in technical vocabulary. It often consists of word
types since only one or two members of a word family may be technical (Coxhead, 2017).
That is, where a word family consists of more than one related word type such as walk,
walks and walking, technical vocabulary in a particular field usually contains one or two
word type(s) from the word family (Nation, 2016; Nation & Webb, 2011). Further, a focus on
word types over word families ensures that words, which might be removed from analysis if
word families are the unit of analysis, are retained (Ha & Hyland, 2017). Also, Coxhead
(2017) states that proper nouns appear as technical language in disciplines such as medicine
and history, and in trades such as carpentry. Another important language component which
may form part of technical language is multiword units. These are phrases ‘made up of
words that frequently occur together’ (Nation, Shin, et al., 2016, p. 71) including two word
collocations and three or more word bundles (Coxhead, 2017). Identifying technical
vocabulary provides information about the nature of specialised language.
2.2.2 Corpus analysis to examine technical vocabulary
Corpus analysis provides a way to identify more technical or cryptotechnical words and
phrases. One method, used in the trades and academia, for identifying technical vocabulary
is to compare a specialised corpus with a general language corpus (Chung & Nation, 2004;
Coxhead, 2017) such as Nation (2020) BNC/COCA word family lists (Coxhead et al., 2020). In
the initial comparison, specialised vocabulary is immediately highlighted because it does not
appear in general corpus lists (Coxhead, 2017; Nation, Coxhead, et al., 2016). From there, an
analysis is made of the remaining words which appear in both lists to identify technical
words for the specialist area being studied (Coxhead, 2017). This method has been used
previously to create wordlists of technical vocabulary in carpentry (Coxhead et al., 2016;
Coxhead et al., 2020), plumbing (Coxhead & Demecheleer, 2018; Coxhead et al., 2020),
18
fabrication (Coxhead et al., 2019; Coxhead et al., 2020), and automotive trades (Coxhead et
al., 2020). The technical wordlists were used to identify range of words (just found in one
trade, or across all four); word frequency in each trade; and types of technical vocabulary
including single words, multiword units, abbreviations and proper nouns (Coxhead et al.,
2020). Identifying technical vocabulary to create a wordlist provides useful information
about the nature of language.
Creation of specialist wordlists from a corpus also allows the percentage of technical
vocabulary in a text to be established (Coxhead, 2017; Nation, Coxhead, et al., 2016). This
was done in each of the trades. Table 2.2 gives the coverage for all four trades and for an
academic medical textbook to show typical technical vocabulary load in a range of fields. For
example, carpentry shows that 10.69% of spoken language consists of technical vocabulary.
In the written corpus, this figure is almost four times higher. Essentially, one in ten words in
the spoken corpus is technical and in the written corpus, this figure is two words in five. The
table shows that there is typically three to four times more technical vocabulary in written
corpora than in spoken corpora. A written academic textbook has similar coverage to these
trade texts.
Table 2.2
2.2 Coverage of technical language in written and spoken corpora
Technical vocabulary list Spoken corpus Written corpus
Carpentry 10.69% 38.35% Plumbing 11.59% 34.48% Fabrication 9.18% 30.47% Automotive 12.75% 37.44% Anatomy textbook 37.6%
Table 6.5: Coverage results for all four LATTE technical word lists, abbreviations, and proper nouns from
Coxhead et al. (2020) is adapted here. The figure for the anatomy textbook is from Chung and Nation (2004).
In aviation, research of technical vocabulary and coverage is limited. Two studies examine
technical vocabulary. The first study by Pannebecker (2019) identified examples of content
words which were categorised as nouns (runway, heading, tower, pilot, American, sir),
numerals (zero, one, two, three … thousand), adverbs (now, up), interjections (o, ah), verbs
(cleared, turn) and adjectives (heavy, left, right, okay). The second study examined the use
of twelve general English words which are technical words in aviation e.g. taxi, take-off,
19
descend and climb. Hüllen (1981) described these words as having a scientific slant in the
specialist context of air traffic control communication. In this context, the words describe
experiences exactly and there is little flexibility for manipulating their meaning. Hüllen
(1981) concludes that general English words in aviation English become specialist words, not
because of frequency, or preferred grammar or style, but mostly because of semantic use
and context. This description fits with what Fraser (2009) calls cryptotechnical language,
which is vocabulary that includes high, medium and low frequency words which look like
everyday words, but have a technical meaning that may not be immediately obvious (see
also, Coxhead (2017)). In the study by Lopez, Condamines, Josselin-Leray, et al. (2013)
proper nouns were one of several items removed from the corpus, suggesting that technical
vocabulary may have been contained in the data eliminated from their research (discussed
in Section 2.2.1). In terms of coverage, a study by Shin and Kim (2005) found pilots and
controllers estimated standard phraseology made up 70% of their communication.
However, no quantitative analysis has been done of aviation radiotelephony which shows
the extent of standard phraseology or technical vocabulary in aviation.
The composition and coverage of aviation technical vocabulary in aviation radiotelephony
communication has not been established. Although some aviation radiotelephony technical
vocabulary has been described, a study such as those completed in the trades has not been
done. Further, the coverage of technical vocabulary in aviation radiotelephony has not been
established. This study seeks to investigate the nature of technical vocabulary contained in
aviation radiotelephony communication, and to establish its coverage in simulated
emergency situations.
2.3 Factors that influence the use of technical vocabulary in aviation
There are a range of factors that may influence the use of technical words in aviation:
language background, experience and technical knowledge. The United Arab Emirates is a
multilingual environment with pilots and controllers from a range of language backgrounds.
Language backgrounds are a source of miscommunication in aviation radiotelephony. For
example, Kim and Elder (2009) identified an unusual situation in Korean airspace where a
native English speaking (NES) pilot asked a non-native English speaking controller for a
diversion to another airport. The pilot’s request was long, containing a lengthy plain
language explanation of why they needed a diversion. As a result, the controller did not
20
immediately understand the request. A possible reason for the long explanation could be
‘justification’ (Moder, 2013; Sänne, 1999) derived from a need to explain an unexpected
request and recognition of the extra workload it creates for controllers (Moder, 2013).
Interviews with non-native English speaking (NNES) aviation personnel found that they
thought the explanation was wordy, unnecessary and the request could have been made
using standard phraseology (Kim & Elder, 2009). Bieswanger (2013) also found that a NES
controller used wordy, confusing language which could have been more easily
communicated with standard phraseology.
In a later study by Kim and Elder (2015), also in South Korea, aviation personnel reported
that experience, technical knowledge and situational awareness were essential elements of
successful communication in aviation. They were critical of the language proficiency
requirements contained in ICAO (2018) since they do not address these three elements.
Language tests in South Korea do not address them either. Consequently, the Korean
aviation language test had meant personnel with knowledge and experience in aviation
were disadvantaged and/or lost their jobs. These experienced personnel would be replaced
by younger less experienced professionals with higher language proficiency but lacking in
knowledge. Such a situation could create another risk to aviation safety. Further, there was
no requirement in the testing policy for NES to adjust their language use to meet the needs
of aviation in environments where language proficiency varies. Participants in the study
stated that NES’s tended to overuse plain language and this created miscommunication (see
Day (2004); Howard (2008)). Such language use results in extended communication to clarify
meaning (Field, 2020).
In another study, Kim (2018) found that a lack of technical knowledge was a source of
miscommunication. Lack of knowledge on the part of a controller resulted in an interaction
with a pilot which lasted more than 17 minutes and consisted of more than 100
transmissions. Both interlocuters were NNES, but the pilot had low English language
proficiency and excellent technical knowledge. Conversely, the controller had good English
language proficiency, but poor technical knowledge. Kim (2018) showed that the pilot
request for a diversion could have been solved if the controller had the requisite technical
knowledge. In interviews, aviation personnel were critical of the lack of technical knowledge
of the controller and felt that this was the cause of miscommunication rather than the
21
pilot’s language proficiency. Good general language ability does not predict success in
understanding aviation English radiotelephony (Moder & Halleck, 2009; Trippe, 2018).
A study by Knoch (2014) found that pilots were critical of speakers who lacked technical
knowledge or were not fluent in radiotelephony. This investigation asked pilots, air traffic
controllers and language experts to appraise the language use of aviation personnel in
recordings. One goal in the study was to identify what aviation personnel thought was
important to successful and safe communication in radiotelephony. The aviation personnel
judged the speakers’ ability to transition from standard phraseology to plain language as
they would be required to do on the job. Aviation experts expected that users could use
both interchangeably (Elder et al., 2017; Kim, 2018; Knoch, 2014) and were critical of a user
who did not have the flexibility to smoothly transition from one to the other. They were also
critical of speakers who lacked the technical knowledge to carry out the task (Knoch, 2014).
This section focused on research that identified several areas of potential
miscommunication each resulting in language use with different proportions of standard
phraseology or plain language. The first is the difference in language use by NNES and NES
aviation personnel. The second is technical knowledge or a lack of it. The third is the ability
to transition smoothly from standard phraseology to plain language. Deviations from
standard phraseology are a precursor to miscommunication (Day, 2004; Howard, 2008) and
language proficiency does not predict success in aviation radiotelephony. Finally,
miscommunication leads to the need for clarification of meaning. This study seeks to
identify what controllers in the UAE regard as causing language variation which leads to
miscommunication.
2.4 Summary of literature review
This chapter has outlined the nature of aviation radiotelephony by first examining standard
phraseology which is the language mandated by ICAO for use in routine situations. Next, the
chapter explained plain language and found its definitions unclear and contradictory. The
literature is also unclear about how standard phraseology and plain language are combined
in aviation radiotelephony, but it is generally accepted that they are intertwined. The
literature on their use in emergencies is likewise contradictory, from more plain language
being used in emergencies to standard phraseology being enough. At the same time, air
traffic controllers must be silent during emergencies. The chapter also explored previous
22
corpus research on aviation radiotelephony and reasons for miscommunication related to
the use of standard phraseology and plain language. This current research proposes to
investigate the nature of technical vocabulary in aviation radiotelephony in an air traffic
control simulator, the extent to which it is used and the factors that affect its use in the
workplace. Chapter 3 outlines the methodology used in this research.
23
Chapter 3 Methodology
This chapter contains three sections. The first section is the background which outlines the
location of the research, the participants and ethics. The second section presents the data
collection methods and includes the principles of corpus development for the spoken and
written corpora, followed by the data collection method for interviews. The third section
identifies the data analysis undertaken. It describes problems encountered with the tools
for analysis of aviation radiotelephony language. Next, it explains tagging of proper nouns
and numbers for retention and comparison between corpora. Then, the principles used to
create a technical word and number list are outlined. The methodology for keyword analysis
is presented. Finally, the interview data analysis for themes is explained.
3.1 Background
Data collection for this research took place at the GAL ANS Training Centre, Al Ain, United
Arab Emirates. The spoken corpus was created from recordings of two emergency training
sessions in air traffic control simulators at the centre. Controllers were from Ghaf
Aerodrome and Sandy Aerodrome. Interviews included controllers from Desert and Dune
airports.
3.1.1 Participants
A total of nine participants took part in this research. They were chosen by convenience
sampling (Friedman, 2012; Rothwell et al., 2016). Eight were air traffic controllers who
arrived at the training centre to do emergency continuation training and were asked if they
would be willing to take part in the research. The final participant was asked to take part in
the research during an unrelated meeting and an interview was scheduled for a later date.
Two Ghaf controllers and one Sandy controller were recorded in the simulator; and
interviews were conducted with four more Ghaf controllers and one more controller each
from Dune and Desert Airports. The participants were all licensed tower controllers who
worked in the UAE. Seven of the controllers worked at military bases (Ghaf and Sandy
aerodromes), while the remaining two worked at civilian airports which handle military
traffic (Dune and Desert Airports). Their experience ranged from five to thirty-nine years
and they had worked in the UAE between one and twelve years.
24
Table 3.1
3.1 Research participants
First language (L1) Number of participants
Second language(s) (L2)
Places worked
Arabic 3 English UAE
Arabic 1 English UAE, Turkmenistan, Pakistan, Kazakhstan
Arabic 1 English
Comprehension only: Hindi
UAE
English 1 N/A USA, Afghanistan, UAE
English 1 Spanish USA, Korea, Japan, Italy,
Honduras, Iraq, Afghanistan, UAE
Swedish 1 English, German,
French
Sweden, Estonia, Latvia, Lithuania, Nigeria,
Namibia, Saudi Arabia, UAE
Estonian 1
English
Comprehension only: Russian,
Finnish
Estonia, UAE
Table 3.1 shows the participants come from a range of language backgrounds. Eight out of
nine controllers speak more than one language. Seven of the participants speak English as a
second language and one speaks English only. Of those who have worked outside the UAE,
two have worked in English-speaking countries, and all have worked in non-English speaking
countries. Three participants took part in the recorded simulator sessions on two separate
occasions, two Emirati controllers and one American controller. All participants took part in
interviews.
25
3.1.2 Ethics
The Victoria University of Wellington Human Ethics Committee approved this research
(reference number: 0000027733) (see Appendix A). In order to protect the identity of
participants, pseudonyms are used for their names and workplaces.
3.2 Data collection
The first section below discusses corpora collection and the second focuses on the interview
data. Two corpora were created for quantitative analysis. The first was based on data
gathered in air traffic control simulators and the second was developed from the main
written texts for aviation radiotelephony. Qualitative data was gathered from interviews
with controllers.
3.2.1 Spoken corpus
Simulators have built-in recording equipment which was utilised to record the training
sessions. Table 3.2 shows the five different emergencies recorded. Ghaf Aerodrome
included three emergencies shown in column three. There were two controllers: a tower
controller who controlled all aircraft entering, exiting, landing and taking off on the runway;
and a ground controller who controlled all aircraft on taxiways and aprons. The Sandy
Aerodrome controller worked alone and covered ground and tower control tasks. The total
number of running words in each corpus was 1749 tokens in Ghaf and 1433 in Sandy. This
number of tokens makes these corpora very small in a field of academic study where a
corpus of approximately 110 000 words is regarded as small (Prado & Tosqui-Lucks, 2019).
Consequently, the findings related to the spoken corpora are not generalisable to a larger
population. In this study, corpus analysis is combined with qualitative interview data to give
a better understanding of the language used in Ghaf and Sandy Aerodromes only. A bigger
study is needed to verify the results of this research.
26
Table 3.2
3.2 Ghaf and Sandy Aerodrome spoken corpora emergencies
Air Traffic Control
Unit
Length of exercise
Emergency Controllers
Ghaf Aerodrome
90 minutes
1. Smoke in cabin 2. Engine flame-out 3. Brake failure
2 controllers: one ground controller; one tower controller
Sandy Aerodrome
48 minutes 1. Co-pilot incapacitated 2. Bird strike/engine on
fire
1 controller – working as both ground and tower controller
Prior to analysis, the spoken corpus was prepared according to the protocols below:
1. The start of each emergency was signalled by the words: Mayday or Pan-pan (GCAA,
2018; ICAO, 2007, 2016a, 2016b), so all transmissions including, and after these
words were included in the corpus. Transmissions prior to mayday or pan-pan were
not included.
2. One item that was corrupted in recording was replaced in the line ** fuel endurance
in the Ghaf corpus. This was changed to 2 hours fuel endurance because 2 was
mentioned in a response that followed.
3. False starts e.g. traf traffic were retained.
4. Changes in instructions were retained e.g. They're going to relocate to/ actually if
you'd like to go to Delta, you can follow the aircraft onto the runway after he lands
(Sandy Aerodrome, 33:23).
5. Greetings and politeness markers such as: Sir, thankyou and good day were retained.
6. Marginal words were retained such as um, ah, aah. Contractions and colloquial
pronunciations (gunna for going to, ya for you) were retained (Nation, 2016).
3.2.2 Written corpus
UAE and international documents were used to create a written corpus. The local (UAE)
General Civil Aviation Authority (GCAA) CAAP 69 UAE Radiotelephony Standards document
(GCAA, 2018) and ICAO Document 9432 Manual of Radiotelephony (ICAO, 2007) were
combined just as Lopez, Condamines, Josselin-Leray, et al. (2013) did in their study. Since
the recordings were made in a tower simulator, the written corpus contained language
27
related to tower control only, in contrast to Lopez, Condamines, Josselin-Leray, et al. (2013)
whose corpus included all types of air traffic control. The principles used in establishing the
written corpus are outlined below:
1. Only the chapters related to tower control were included (see Table 3.3).
Table 3.3
3.3 Chapters from ICAO and GCAA documents included in the written corpus
GCAA CAAP 69 ICAO Doc 9432
Chapter 2 General procedures and
phraseology, Chapter 3 Aerodrome control,
Chapter 7 Distress and urgency, and
Chapter 9 Vehicle procedures and
phraseology (GCAA, 2018).
Chapter 2 General operating procedures;
Chapter 3 General phraseology; Chapter 4
Aerodrome control aircraft; Chapter 5
Aerodrome control: vehicles; Chapter 9
Distress and urgency procedures and
communications failure procedures;
Chapter 10 Transmission of meteorological
and other aerodrome information; and
Chapter 11 Miscellaneous flight handling
(ICAO, 2007).
2. Phrases related to approach or area control were not included. For example, descend
to flight level two five zero is not relevant to tower control because it is said by an
approach controller;
3. Standard phraseology for use between a vehicle driver and a controller was included,
but standard phraseology for use between a vehicle driver and aircraft was excluded;
4. Phrases are given in block capitals in the original documents and capitalisation was
retained;
5. If an entry identified more than one possibility, then all possibilities were included.
For example: RIGHT (or LEFT, or NOSE) WHEEL APPEARS UP (ICAO, 2007capitals in
original) became:
RIGHT WHEEL APPEARS UP
LEFT WHEEL APPEARS UP
28
NOSE WHEEL APPEARS UP;
6. The word ‘or’ was removed between two possible options and both were included as
two separate items. For example, the following text became two separate lines of
text in the corpus:
RUNWAY 09 CLEARED TO LAND FOR FULL STOP G-CD
or
G-CD MAKE ANOTHER CIRCUIT REPORT DOWNWIND (capitals in original);
7. Duplicates were retained e.g. FASTAIR 345 WILCO (capitals in original) appeared
three times on one page and was kept in the corpus;
8. All numbers and proper nouns were included.
3.2.3 Interviews
The second set of data was interviews with nine controllers, including six from Ghaf
Aerodrome, one from Sandy Aerodrome and two from two civil airports, Desert Airport and
Dune Airport. Interview questions were designed to find out the source of differences in the
language used by controllers. Ten questions asked about the participants’ background, the
context of their work, their opinions about sources of miscommunication and about training
(see Appendix B). The interviews were semi-structured (Friedman, 2012) and conducted in
English. Interviews ranged in length from 6 ½ minutes to 44 minutes. Recording the
interviews allowed us to focus on the questions, and made the process less intrusive
(Friedman, 2012). A mobile phone was used and tested prior to the first interview to ensure
the quality of recording would be adequate (Duff, 2012). Initially, seven interviews were
completed, but two further interviews followed with controllers from Desert and Dune
airports. The extra interviews were with civil aviation air traffic controllers to widen the
scope of the research and find out if civil controllers experienced the same issues as military
controllers. The interviews were transcribed orthographically (Adolphs & Carter, 2013).
Repetitions were included. Transcription only included information which would answer the
questions asked (Loewen & Philp, 2012; Révész, 2012).
3.3 Data analysis
This section focuses on the creation of the word and number list, keyword analysis and
interview analysis.
29
3.3.1 Adapting tools for aviation language
Initially the Lextutor Range programme was used to analyse the written and spoken corpora
(Cobb, n.d.). However, several difficulties arose from the results. In Lextutor, numbers are
not included in the output and proper nouns are listed, but their meaning and purpose in
relation to aviation required specialist knowledge to interpret or could not be identified.
Here is an example of proper nouns, numbers, abbreviations and aviation alphabet from the
written corpus in this study:
FASTAIR 345 CLEARED TO KENNINGTON, VIA A1 FL 280 WICKEN 3 DELTA DEPARTURE,
SQUAWK 5501 (ICAO, 2007, p. 2.13).
The text is a clearance given by a controller to a pilot before the aircraft engines are started
(ICAO, 2007, p. 2.13) and the numbers represent part of a callsign, a flight level, a departure
route and a squawk code (ICAO, 2007, 2016b). Lextutor produced:
fastair number cleared to kennington via a number fl number wicken number delta
departure squawk number
The composition of each number is not shown in this result. The analysis also shows that
when proper nouns and numbers are removed, the text is halved from sixteen tokens to
eight:
cleared to via a fl delta departure squawk
If the abbreviation ‘fl’ and aviation alphabet letter ‘a’ are removed, the text is further
reduced as follows:
cleared to via departure squawk
The sentence ‘cleared to via departure squawk’ makes no sense in radiotelephony. The
removal of numbers, proper nouns and abbreviations has significantly changed the meaning
and quantity of this text and it no longer represents the original corpus.
Further analyses of proper nouns, numbers, aviation alphabet and abbreviations were
carried out on the written corpus with Wordsmith (Scott, 1996), Lextutor (Cobb, n.d.),
AntConc (Anthony, 2019) and Range (Heatley et al., 2002). Analyses included:
30
• Wordlists with AntConc and WordSmith;
• N-gram and concordance analyses with Lextutor and AntConc. An N-gram is a
sequence of words and N stands for the number of words in the sequence (Nation,
Shin, et al., 2016).
• Range analysis based on Nation (2020) BNC/COCA word family lists using the Range
Programme developed by Heatley et al. (2002). This programme showed how proper
nouns and aviation alphabet were distributed throughout the lists (Nation, 2016).
The results of analyses with these tools were inconsistent. Numbers and proper nouns with
the same purpose were either counted separately or lost, meaning that comparisons across
corpora were difficult to make. The meaning of numbers was unclear or items appeared in a
list according to the number rather than the information conveyed. This means, for
example, that N-grams with the same meaning were listed separately throughout the N-
gram list. Ultimately, corpus tools were able to identify some information, but this was
often limited and comparisons of proper nouns, numbers, abbreviations and aviation
alphabet between corpora was inconclusive.
3.3.2 Tagging the corpora to retain proper nouns and numbers
As a consequence of the inconclusive results with the corpora in their original form, the
written and spoken corpora were manually tagged to retain data and make the corpora
comparable. The tags replaced the proper nouns, numbers and aviation alphabet that they
represent. Scott and Tribble (2006) used a similar method in which they tagged parts of
speech by adding a letter(s) to denote that item, for example, THE_DET, OF_PRP (the
determiner, of preposition). In the current study, tags replaced proper nouns and numbers
with the same meaning. Such items were identified and categorised by using the ICAO
(2016b) Document 4444 Procedures for Air Navigation Services: Air Traffic Management.
Tagging retained all items in the written and spoken corpora and had the dual benefit of
allowing comparison across corpora while ensuring that as much information as possible
could be extracted in spite of the small size of the sample.
Table 3.4 gives an example of a tagged transmission. The information contained in each
column is explained below:
31
• The first column contains the transmission broken down into parts. The meaning of
proper nouns and numbers was found in ICAO (2016b) and presented in column two
with the formatting from the original document. Italicised items in brackets are
substitutable; and phrases in capital letters do not change.
• The tags created are given in column three. For example, FASTAIR 345 is an aircraft
callsign (ICAO, 2016b) shown in italics and brackets. The words CLEARED TO do not
change. FASTAIR 345 is not comparable across corpora, and ‘aircraft call sign’ would
be counted as three unrelated words in corpus analysis.
• The tag (ACCALLSIGN) replaced FASTAIR 345 in column three.
The tags replaced proper nouns and numbers in the phrase, so the resulting text was:
(ACCALLSIGN) CLEARED TO (AERODEST), VIA (SIGPOINT) FLIGHT LEVEL (FLNUMBER)
(STANDARDDEP) DEPARTURE, SQUAWK (SSRCODE).
32
Table 3.4
3.4 Establishing tags for proper nouns and numbers for a single transmission in the written corpus
Phrase Appearance in ICAO (2016b) Tag (IN BRACKETS)
FASTAIR 345 CLEARED TO (aircraft call sign) CLEARED TO
(ICAO, 2016b, p. 12.13)
(ACCALLSIGN) CLEARED
TO
KENNINGTON (aerodrome of destination) (ICAO,
2016b, p. 12.21)
(AERODEST)
VIA A1 VIA (route and/or significant
points) (ICAO, 2016b, p. 12.14)
VIA (SIGPOINT)
FL 280 FLIGHT LEVEL (number) (ICAO,
2016b, p. 12.13)
FLIGHT LEVEL
(FLNUMBER)
WICKEN 3 DELTA
DEPARTURE
(standard departure name and
number) DEPARTURE (ICAO,
2016b, p. 12.16)
(STANDARDDEP)
DEPARTURE
SQUAWK 5501 SQUAWKING (SSR code) (ICAO,
2016b, p. 12.29) or SQUAWK (code
or IDENT) (p. 12.34) or SQUAWK
(code) (p. 12.39)
SQUAWK (SSRCODE)
The written and spoken corpora were tagged. Ten proper nouns were classified into four
categories and assigned ten tags. Aviation alphabet letters were assigned a single tag; and
numbers were classified into twenty categories with eighteen tags (see Appendix C). The
tags allow comparisons across corpora.
3.3.3 Identifying technical vocabulary in aviation radiotelephony
The Heatley et al. (2002) Range programme was used with the BNC/COCA word family lists
to establish technical vocabulary. The BNC/COCA word family lists is a set of 29 lists, 25 of
which are based on frequency and range data, and four supplementary lists of proper
nouns, marginal words, transparent compounds and acronyms (Nation, 2018). Range was
33
used to identify a list of technical aviation words, numbers and acronyms. Several steps
were followed to identify words that are technical aviation language:
1. Word types were used as the unit of analysis for the reasons outlined in Chapter 2
(Coxhead, 2017; Ha & Hyland, 2017);
2. The tags developed for comparison above were added to an aviation Baseword list.
They represent technical radiotelephony vocabulary and act as content words which
convey meaning (Nation, 2016, p. 89). For example, a pilot needs to know numbers
for which runway to land on, what altitude to climb to, what gate to use or what
should be entered into the altimeter for correct altitude readings (Estival, 2016).
Proper nouns provide information about such items as destinations, navigation
points or aircraft type. Tagging ensured proper nouns and numbers were retained
and counted in the corpora (Nation, 2016);
3. Any words in the corpus, but not in the BNC/COCA lists were analysed to establish if
they should be included in the radiotelephony list (Nation, 2016; Nation, Coxhead, et
al., 2016; Nation & Kobeleva, 2016; Nation, Shin, et al., 2016). Those that were
specific to aviation such as Straight-in, stop-bar, air-taxi and air-taxiing were added
to the radiotelephony list;
4. Other words which occurred in the corpus, but not in the BNC/COCA lists were
added to BNC/COCA lists. For example, co-pilot consists of co- and pilot. Pilot can be
found in Baseword list 3 and has a commonly understood meaning. Co-pilot was
added to Baseword list 7 because co- is identified by Nation (2016, p. 27) as a level 7
‘classical root and affixes’ word;
5. Words which appear in BNC/COCA word family lists were examined to determine if
they had semantic or structural properties which differed when used in aviation
radiotelephony. Request is an example of a word that differs from the general
English sense for the word, both semantically and grammatically.
a. The use of request in phrases such as request start-up from the written corpus
was compared to sentences from the website:
https://sentence.yourdictionary.com which returned long lists of sentences used
to verify the semantic use in general English. In the sentence request start-up,
request means ‘I’m asking you for permission’ which is a slightly altered version of
34
its general English meaning ‘to ask for’. When considered semantically, request
may be labelled lay-technical (Fraser, 2009) or least technical (Ha & Hyland, 2017).
b. Request is more technical when its syntactic use is considered. The syntax used in
aviation radiotelephony communication is an imperative form which did not
appear in the sentences from the above website. The form of request start-up
confirms request is technical vocabulary. Other verbs were used in a similar way,
such as report and require;
6. Words which are mentioned in the ICAO documents to be used in a particular way or
with a particular meaning were included in the aviation list e.g. cleared, take-off,
break (GCAA, 2018; ICAO, 2007, 2016a, 2016b);
7. High frequency word types (from the first 1,000 and second 1,000 BNC/COCA lists)
were examined if they appeared more than would be expected in general English,
since these are likely to be technical vocabulary (Nation, 2013, 2016; Nation &
Webb, 2011).For example, continue, station, expect;
8. The high frequency words often made up multiword units including: feet, to, mile,
close, appear (Barshi & Farris, 2013; ICAO, 2016b) e.g. ALTNUMBER feet, cleared to
land, appear up. In this study, MWUs were treated as ‘non-decomposable word-like
units’ (Nation, 2016, p. xii) and were counted as single words (Nation, Coxhead, et
al., 2016; Nation, Shin, et al., 2016). The multiword units were created in the corpora
by removing the space between words before analysis e.g. clearedtoland.
The nature of technical vocabulary in the aviation radiotelephony simulator emergencies
was identified by examining items in the word and number list. Further, technical
vocabulary coverage of the spoken corpora was established using the Heatley et al. (2002)
Range programme. The nature and coverage of technical vocabulary in this study is
presented in Chapter 4. The above steps identified vocabulary as technical (or not) and
further analysis, in terms of frequency such as that done in the trades (Coxhead et al., 2020)
or in terms of degree of technicality such as that done in a study of academic finance
language (Ha & Hyland, 2017) was not done. A larger study is required to establish
frequency and degree of technicality of the vocabulary used in aviation radiotelephony.
35
3.3.4 Keyword analysis for language use
Keywords are those words which occur unusually frequently when a corpus is compared to
a reference corpus (Scott & Tribble, 2006). Keywords provide information about how the
vocabulary in the study corpus differs from the reference corpus (Scott & Tribble, 2006).
Scott and Tribble (2006) use the Shakespeare play Romeo and Juliet to examine the
information revealed through keyword analysis by using increasingly specialised reference
corpora in order to establish how the results change. They examine the play against the
following reference corpora: BNC corpus, a corpus of all Shakespeare plays; a corpus of the
tragedies alone; and finally, a corpus of the complete works of Shakespeare including
poetry. Each of these analyses produced a core list of 26 keywords in the play, but revealed
different kinds of information according to the reference list used. Scott and Tribble (2006)
and finish by examining a technique developed by Culpeper (2002). Culpeper examined
Romeo and Juliet using the play itself as the reference corpus to examine the language used
by each character. Corpora were created for each character and comparison produced
keywords from which Culpeper was able to make inferences about language use by
individual characters.
Culpeper’s method was used in the keyword analysis in the current research to identify
language differences in each of the aerodromes. The reference corpus was the written and
spoken corpora combined. The spoken Sandy corpus and the spoken Ghaf corpus were
compared individually to the reference corpus to establish language differences between
the units. For keyword analysis to work, the reference corpus should be five times larger
than the text to be analysed (Scott & Tribble, 2006). Table 3.5 shows that the reference
corpus (7439 tokens) is five times the size of the Sandy corpus and 4.25 times as large as the
Ghaf corpus. Analysis allowed closer examination of language differences between
controllers in each of the units.
Table 3.5
3.5 Size of corpora for keyword analysis
Corpus Reference Corpus Ghaf Aerodrome Sandy Aerodrome
Written corpus
Tokens 7439 1749 1433 4257
36
The corpora were examined using keyword analysis in Scott (1996) Wordsmith programme.
Wordsmith produces a figure for keyness for each of the words identified and the numbers
are interpreted as follows:
below 0 not trustworthy
0-2 only worth a bare mention
2-6 positive evidence
6-10 strong
more than 10 very strong (Scott, 2019).
Keyword analysis was used to identify differences in the use of plain language in the two
aerodromes and the results are given in Chapter 4.
3.3.5 Interview analysis
The transcribed interviews were analysed initially for interviewee agreement or
disagreement with the questions posed. The most relevant themes were then selected for
further analysis according to what emerged from the data (Révész, 2012). This process
involved reading through the interviews several times and annotating the transcriptions
until themes started to emerge. Interview quotes were categorised according to theme.
Categories identified were: attitudes towards the use of standard phraseology; beliefs about
language use and training; differences between the simulator and the workplace;
multicultural context of the workplace and miscommunication; native English speakers’
contribution to miscommunication; and clarification of meaning to resolve
miscommunication.
3.4 Summary of methodology
The quantitative analyses conducted were used to create an Aviation Radiotelephony
Technical Word and Number List of technical aviation vocabulary and multiple word units
which served three purposes. First, the technical vocabulary contained in radiotelephony
was identified. Second, the list was used to establish the extent to which technical
vocabulary was used in the spoken corpora. Third, a keyword analysis identified differences
in the use of plain language between Ghaf and Sandy aerodromes. The interviews were
analysed for themes which help explain the factors affecting the use of technical vocabulary
37
in the corpora and in the workplace. The results of these analyses are presented in Chapter
4.
38
Chapter 4 Results
This chapter is divided into three parts which answer each of the research questions in this
study. The first research question is answered by examining the Radiotelephony Technical
Word and Number List. The second research question is answered by establishing the
coverage of technical vocabulary in the spoken corpora of aviation radiotelephony in air
traffic control emergency simulator training. The third research question is answered using
keyword analysis of the spoken corpora and themes derived from the interview data to
examine three factors that influence the use of technical vocabulary in speaking.
4.1 RQ: What is the technical vocabulary of aviation radiotelephony in emergency training in
the simulator?
The Aviation Radiotelephony Word and Number List (ARWNL) totalled 577 items and
showed that there was a range of technical vocabulary used in emergency training. In
addition to the 10 proper noun categories, 18 number categories and aviation alphabet
category identified through tagging (totalling 29 tags), the ARWNL contains 548 items
including: 301-word types; and 247 multiword units (MWUs). A total of 243 items
representing 42% of the list appeared once. A high percentage of single items is not unusual
since the BNC corpus includes 40% of them (Scott & Tribble, 2006). The single items were
retained in the wordlist for two reasons. First, they met the criteria for technical vocabulary.
Second, a bigger study is needed to verify their frequency. In the list, 79 proper nouns,
numbers, aviation alphabet and word types and 11 MWUs occurred ten or more times.
Given the size of the combined corpora (including non-technical words) in Table 4.1, (900
items) a frequency of ten or more makes these items very high frequency in comparison to
the corpora size (Nation, Coxhead, et al., 2016). Column 2 of Table 4.1 shows the number of
items, identified as word types in the range programme, in the tagged corpora after
completion of steps 1 to 3 in the identification of technical vocabulary (see Section 3.3.3).
The final column in Table 4.1 gives the number of items after words had been added to
BNC/COCA word lists and items from the word lists were added to the technical word and
number list. Further, the final column includes MWUs. The identification of MWUs
increased the number of items identified by the Range programme from 667 to 900,
suggesting that the language used is more complex once MWUs are taken into account.
39
Finally, the 577 technical items in the list represents 64% of the 900 items in the combined
corpora results.
Table 4.1
4.1 Technical and non-technical vocabulary in corpora
Number of items in tagged corpora using BNC/COCA
word family lists
Number of items in tagged corpora using adapted
BNC/COCA word family lists - includes multiword units
Written corpus 415 434
Ghaf Aerodrome 296 363
Sandy Aerodrome 286 341
Combined corpora 667 900
Table 4.2 is the first 25 items in the list (see Appendix D for more list items). The table is
organised by total frequency (in the final column) and gives the definition of each item and
its frequency in each corpus e.g. the item with the highest frequency was ACCALLSIGN which
is a tag for aircraft callsign, appears in all three corpora and has a total frequency of 676.
Table 4.2 represents a range of vocabulary which are identified in the subsections below.
Note that the table is organised by frequency in the final column. Further technical
vocabulary items can be found in Appendix D which contains items appearing more than 10
times; items appearing more than three times in more than one corpus; items appearing
more than 4 times in the written corpus; and multiword units that appear 3 or more times.
40
Table 4.2
4.2 First 25 word and number types in the Aviation Radiotelephony Word and Number List
Rank Type Definition of tags Written Ghaf Aero
Sandy Aero
Total Freq
1 ACCALLSIGN Aircraft callsign 462 160 54 676
2 VECALLSIGN Vehicle callsign 63 26 94 183
3 AVALPHABET Aviation alphabet 84 26 43 153
4 UNCALLSIGN Unit callsign e.g. Ghaf or Sandy 81 32 18 131
5 TOWER Type of controller; or building 53 9 62 124
6 TO Never use before a number 88 10 24 122
7 NNUMBER Number 52 38 24 114
8 GROUND Type of controller 29 52 0 81
9 ROGER
All of last transmission received (ICAO, 2016a, 2016b) 36 12 26 74
10 ACTYPE Type of aircraft e.g. Boeing, Cessna 55 9 8 72
11 RUNWAY 32 6 15 53
12 VIA 49 2 2 53
13 ALTNUMBER Altitude number e.g. 3 000 feet 47 3 0 50
14 FEET
Distance (horizontal or vertical) e.g. altitude 3 000 feet 48 2 0 50
15 REQUEST 49 1 0 50
16 QNH Barometric pressure at sea level (Estival & Farris, 2016) 49 0 0 49
17 QNUMBER QNH number 49 0 0 49
18 REPORT 40 1 0 41
19 TAXIWAY Road for aircraft to move around aerodrome 30 4 5 39
20 WIND 29 3 1 33
21 MAYDAY Emergency call 22 7 3 32
22 POSQUEUE Position in queue 19 12 1 32
23 WINUMBER Wind number (degrees) 29 3 0 32
24 WISPEED Number for wind speed (knots) 29 3 0 32
25 KNOTS Measure of wind speed 31 1 0 30
41
4.1.1 Proper nouns and semantic categories
There are four proper noun categories in the first 25 items of the technical list. In Table 4.2,
three out of the first four items are proper nouns, which are callsigns used to identify who is
speaking and who they are speaking to. They are the tags: ACCALLSIGN, VECALLSIGN, and
UNCALLSIGN. Item 10 in the table, ACTYPE, is also a proper noun tag for types of aircraft.
Proper noun tags represent a group of items with a particular meaning in aviation. The tags
act in a similar fashion to headwords in word families (Nation, 2016; Nation & Webb, 2011).
In Table 4.2, the tag ACTYPE (aircraft type) shows a total frequency of 72. Examples of
individual aircraft types are not included in the technical list. If they were, they would
appear as they do in Figure 4.1 which shows the 12 aircraft types found in the written
corpus. Aircraft types are common to a particular aerodrome or airport and different types
to those listed were found at Sandy and Ghaf aerodromes.
Figure 4.1
4.1 A selection of aircraft types belonging to the proper noun category aircraft type (ACTYPE)
ACTYPE
Boeing 737 Boeing 747 Boeing 767 Boeing 777 B747 B737 B757 C172 Cherokee Airbus A320 Learjet Seneca
4.1.2 Numbers and semantic categories
Six out of the first 25 items in the technical vocabulary list in Table 4.2 are numbers with the
tags: NNUMBER, ALTNUMBER, QNUMBER, POSQUEUE, WINUMBER and WISPEED. Each tag
is a number category with a specific meaning and format. The first tag, NNUMBER, retains
numbers in the corpus which would be used as a layperson might understand them e.g.
42
Gate 2 would be Gate NNUMBER. NNUMBER is included as technical vocabulary because of
the standard operating procedures related to its use. In the case of a gate number, for
example, a controller might need to know which aircraft type can park at a particular gate or
how an aircraft should be directed to get there. Appendix C shows that numbers may
appear in a variety of formats such as four-digit numbers for a radar code or numbers
including a decimal point for radio frequencies.
A key point here is that the same numbers can be semantically different. Two examples are
the tags WINUMBER and HDGNUMBER which have a total frequency of 32 and 11 in the list.
Both sets of numbers are degrees, but wind is the direction from which wind comes while a
heading is the direction an aircraft goes towards. Figure 4.2 identifies some of the numbers
from the written corpus which were found under each tag.
Figure 4.2
4.2 A selection of numbers represented by the number categories HDGNUMBER and WINUMBER
HDGNUMBER
090 160 190 270 280 360
WINUMBER
080 190 250 260 270 290 360
4.1.3 Alphabet letters
The final tag category in the corpora was AVALPHABET. This category includes the twenty-
six letters of the aviation alphabet shown in Figure 4.3. The aviation alphabet letters were
used in the corpora to identify taxiways. They can also be used as part of callsigns or as part
of navigation points on aeronautical charts. These uses were already accounted for in the
proper noun tags.
43
Figure 4.3
4.3 Aviation alphabet letters represented by the tag AVALPHABET
AVALPHABET
Alpha Bravo Charlie Delta Echo Foxtrot Golf Hotel India Juliet Kilo Lima Mike
November Oscar Papa Quebec Romeo Sierra Tango Uniform Victor Whisky Xray Yankee Zulu
4.1.4 Acronyms
Acronyms were another category of technical vocabulary identified in the corpora. The only
one in Table 4.2 is QNH which is the barometric pressure at sea level (Estival, 2016). Pilots
use the QNH number to set their instruments correctly so that they fly at the right level.
QNH and QNUMBER were used in the simulator exercises, but before mayday or pan-pan
which signalled the beginning of the emergencies. Another acronym found in the written
corpus (twice) and Ghaf aerodrome corpus (nine times) was POB (persons on board), but no
others appeared more than ten times in this study. Other acronyms that occurred in the list
were: FOD, RVR, ATIS, IFR, VFR, ILS, CAVOK and QDM.
4.1.5 Word types and semantic categories
Word types, including purely technical vocabulary and cryptotechnical vocabulary constitute
the final category of technical vocabulary in the word and number list. Words such as feet
and stand are single word types because family members such as foot or stands did not
appear in the corpora (Coxhead & Demecheleer, 2018). Words with a purely technical
meaning include taxiway (Item 19 in Table 4.2), standby, stopbar, airtaxi, liftoff and
dewpoint. Of these words, only taxiway and standby occurred more than ten times in the
list. The proper nouns, numbers, aviation alphabet and acronyms discussed above
44
constitute the remainder of the purely technical vocabulary. Cryptotechnical vocabulary
(Fraser, 2009) includes tower (item 5, Table 4.2), to (item 6, Table 4.2), ground (item 8, Table
4.2), roger (item 9, Table 4.2) and runway (item 10, Table 4.2); caution (Baseword List 4),
turbulence (Baseword List 5), vacate (Baseword List 8), overcast (Baseword List 10), mayday
(Baseword List 14) and wilco (Baseword List 24). These items were all added to the technical
word and number list. Some cryptotechnical words have more than one technical meaning
including apron, approach, base and tower which are discussed below. Fraser (2009)
suggests that some words have both a technical meaning and are used in the usual sense
e.g. to. The word to is included here because its use is mandated by the General Civil
Aviation Authority in the UAE, which states that, ‘in all messages relating to a climb or
descent to an ALTITUDE, the word ‘to’ shall be used immediately prior to the word
ALTITUDE’ (GCAA, 2018, p. 29 capitals in original). It is also used in its general sense towards
a location.
Some words could be categorised into different groups but they were recorded as a single
word type in the technical list for analysis in the Range programme (Heatley et al., 2002).
For example, the word apron can be an aerodrome location and a type of controller.
Approach is used to mean a type of controller and is part of the final flightpath for aircraft
approaching the runway. It can also be used in its general English sense. There are other
words for which semantic and grammatical differences exist such as base, tower and final.
Categorising words into groups would be useful but is not possible since each word can
appear in the list once.
4.1.6 Multiple Word Units: ICAO standard phraseology, subsidiary phraseology, and local phraseology
This section examines the multiword units (MWUs) in the technical list. The multiword units
include standard (ICAO), subsidiary, and local phraseology. Table 4.3 contains a list of the
eleven MWUs which occurred more than ten times in the technical list. Note the table is
organised by total frequency in the last column.
45
Table 4.3
4.3 Technical multiword units which occur > 10 times in the list
Written Ghaf Sandy Freq
RUNWAY RWYDES 159 8 7 174
CLEARED TO LAND 16 3 7 26
CLEARED FOR TAKEOFF 24 2 0 26
IN SIGHT 18 1 1 20
HOLDING POINT 18 3 0 21
HOLD SHORT (of) 11 3 5 19
REPORT BASE 1 11 0 12
DO YOU HAVE ANY QUESTION 0 11 0 11
ENGINE START APPROVED 0 10 0 10
CONTROL ZONE 10 0 0 10
HOLDING SHORT 10 0 0 10
ICAO standard phraseology was used in the spoken corpora and the written corpus is
composed of standard phraseology. Table 4.3 shows that six MWUs occurred ten or more
times in the written and at least one spoken corpus. These were: RUNWAY RWYDES (rwydes
is the runway number e.g. 02, 18), CLEARED TO LAND, CLEARED FOR TAKEOFF, IN SIGHT,
HOLDING POINT, HOLD SHORT and REPORT BASE. Another MWU which occurred 17 times in
the corpora was touch and go. Ten of those occurrences were in the phrase cleared (for)
touch and go which occurred in the written corpus as cleared touch and go and as cleared
for touch and go in the Ghaf aerodrome spoken corpus. This is essentially the same MWU
since it is only separated using the word for (see Appendix D, Table D.4). Also, two items
appear only in the written corpus: holding short and control zone. Examination of the
spoken corpora scripts suggests that aircraft and vehicles responded to controller
instructions with hold short rather than holding short as appears in the written corpus. It is
likely that control zone did not appear in the spoken corpus because it was not required for
the simulator exercises.
Subsidiary phraseology was found in the Ghaf corpus, and consisted of MWUs specific to the
aerodrome. As stated in Chapter 2, subsidiary phraseology is developed for a standard
operating procedure (SOP) for which there is no ICAO phraseology and can be constituted of
plain language (ICAO, 2007). For example, Do you have any question in Ghaf corpus in Table
46
4.3 is subsidiary phraseology. It was developed at Ghaf aerodrome for a situation for which
there is no existing standard phraseology and forms part of an SOP.
Local phraseology was also found in the Ghaf corpus and is made up of MWUs that replace a
technical word(s) from the written documents. The phrase engine start approved replaces
the standard phraseology start-up approved in the written corpus. Another example is
MWUs with the word close. Close appeared in the spoken corpora 11 times in the MWUs
requesting right close or right close approved (see Appendix D, Table D.4). The word close is
used in American standard phraseology and means circuit in ICAO standard phraseology
(Boschen & Jones, 2004).
A number of air traffic control events did not occur in the spoken corpora. The following
tags and acronyms appeared only in the written corpus: tags were CONAME, AERODEST,
STANDARDDEP, SPROUTE, SSRCODE, QNUMBER, HDGNUMBER, READNUMBER, and
DPNUMBER; acronyms were QNH, RVR, ATIS, CAVOK and VASIS. This finding indicates that a
number of areas of air traffic control were not covered after emergencies were declared
such as: informing pilots about runway conditions, visibility, and providing pilots with a
number so they could be identified on radar; or were not relevant such as company name
(coname) which is applicable to commercial airports rather than military aerodromes. The
language use also reflects the nature of the exercises conducted in the simulator which is
discussed in Section 4.3.1.
4.2 RQ: To what extent is technical vocabulary used in radiotelephony in emergency training
in the simulator?
The technical vocabulary coverage found for the written corpus was understated. Table 4.4
shows that it was composed of 67.74% technical vocabulary, however this corpus is entirely
composed of ICAO standard phraseology, so theoretically is 100% technical language. As
previously stated, some air traffic control events were not covered in the simulator, so
MWUs not required for comparison with the spoken corpora were not identified. This
meant words which would have been part of MWUs remained in the adapted BNC/COCA
wordlist or as single word types in the technical vocabulary list. The frequencies of many
function words in the 1st 1000 words of the adapted BNC/COCA were high for the written
corpus e.g. at (32), of (27), the (24), on (24), for (20), and (19), from (17). These function
47
words are likely to be part of the unidentified MWUs which would increase the technical
vocabulary coverage in the written corpus.
Table 4.4
4.4 Technical vocabulary coverage in the written and spoken corpora
Adapted BNC/COCA
– word frequency
level
Types %
Written corpus Ghaf Aerodrome Sandy Aerodrome
Technical vocabulary 67.74 70.52 51.61
Technical vocabulary made up a significant proportion of each of the spoken corpora. Table
4.4 shows that technical vocabulary was 70.52% and 51.61% of the spoken communication
in Ghaf aerodrome and Sandy aerodrome corpora respectively. In this study, knowledge of
the technical vocabulary is essential to successful communication in emergency exercises in
the simulator.
4.3 RQ: What factors influence the use of technical vocabulary in speaking?
The Sandy controller used 18.91% less technical vocabulary than the Ghaf controllers. This
section examines reasons for why there is a difference in technical language use between
the controllers.
Table 4.5 identifies the aerodromes and airports in this study and the controllers who work
there. Quotes from their interviews are included in the results sections below.
Table 4.5
4.5 Workplaces of controllers interviewed
Workplace Controller Name
Ghaf Aerodrome Mohammed, Nelson, Mansour, Alia, Mariam, Shaikha
Sandy Aerodrome Floyd
Dune Airport Axel
Desert Airport Oliver
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4.3.1 The exercises and purpose of the simulator training sessions
4.3.1.1 The effect of emergency exercises on language
The emergency exercises in each aerodrome differed. The Sandy aerodrome controller
worked on his own as a tower controller. The first emergency was a birdstrike just after
take-off which caused an engine fire. The aircraft immediately returned to the field. There
were two other aircraft, but they remained on the ground throughout the emergency. There
were six different vehicles involved in the emergency including a fire engine, tow truck and
vehicles required for cleanup. The second emergency involved a pilot becoming
incapacitated just after take-off which resulted in the aircraft returning to the aerodrome to
land. Three helicopters were all cleared to land after the emergency was declared. Vehicles
involved in the emergency were a fire engine and an ambulance. In contrast, there were
two controllers for the Ghaf aerodrome, a tower controller and a ground controller. The first
emergency was an aircraft with smoke in the cabin which requested priority landing. Three
other aircraft were included in the exercise. All three requested engine startup, then a
clearance to fly to designated areas. The aircraft were cleared to start their engines but
remained on the ground for the remainder of the exercise. There were three vehicles
including a fire engine and two ambulances (for the five people on board the emergency
aircraft). In the second emergency an aircraft had an engine flameout and immediately
returned to the aerodrome to land. There were two further aircraft in the exercise, one
requested start-up and a clearance for flight and the other was a helicopter awaiting take-
off. A fire engine was the only vehicle, but there were interactions with an emergency base
as well. The final emergency was brake failure of an aircraft that had just landed and needed
to stop on a taxiway. There were six other aircraft in the exercise. Three of them were in the
air and each one interacted with the tower controller several times. Each aircraft was
completing circuits around the aerodrome and requested a low pass, a touch and go, and
circuits. The controller required them to report their position at various places in their
circuits. The remaining aircraft were on the ground waiting for departure and two were
eventually cleared for take-off. There was a fire engine and ambulance in the exercise as
well as interactions with the emergency base.
49
The differences in the type of exercises in each aerodrome had an impact on the technical
language used. These differences can be seen in the frequencies for ACCALLSIGN and
VECALLSIGN in Table 4.2. At Ghaf, aircraft callsigns were used 160 times versus 54 times at
Sandy. Conversely, vehicle callsigns were used 26 times at Ghaf versus 94 times at Sandy.
The impact of the single tower controller at Sandy versus the tower and ground controllers
at Ghaf is reflected in the frequencies of the words TOWER and GROUND. Notably, the word
ground was not used in the Sandy corpus at all. In Table 4.2, the words ALTNUMBER, FEET,
WINUMBER, WISPEED and KNOTS occur because of pilot requests for flight to designated
areas above or below a given height. In response, the controller gave the wind direction
(WINUMBER) and speed (WISPEED). Table 4.3 shows that aircraft were cleared for take-off
twice at Ghaf aerodrome, and not at all at Sandy aerodrome. This language use shows that
there were differences in the exercises themselves, but these differences do not entirely
account for the lower coverage of technical vocabulary for the Sandy controller since one
type of technical vocabulary is largely exchanged for another. Examination of the purpose of
exercises may only partially explain the differences in coverage.
4.3.1.2 The purpose of the training sessions
Controllers in both Sandy and Ghaf aerodromes stated that the overall purpose of training
was to reduce panic, but this purpose was achieved differently. For Ghaf controllers, the
simulator training was designed to reduce communication problems during emergencies by
standardising the language and procedures. The controllers used a written script with the
checklists in the simulator, and practised reading the script to ask pilots for information and
pass it on to emergency services, as Mohammed explains,
[The] emergency situations … today, we tried to do as … standard as much as we
can, like asking for questions, POB, fuel endurance, type of emergency. …. We
have a checklist, but a lot of people don’t follow it, so you will do it your way, I’ll
do it my way (Mohammed).
Once the controllers finished their training, the emergency service personnel would also
receive training which was expected to improve communication in emergencies. Two
controllers explain,
50
we’re going to get all the [emergency services] … and we’re going to train them as
well so that they know how we’re going to start reading it and I think that this will
cut down on a lot of confusion (Nelson).
The other agency which is the fire department, the clinic, … [if] everybody’s using
the same checklist exactly there will be no issue, inshallah (Mohammed).
In contrast, the Sandy simulator session focussed on logistics. The controller practised what
to do in an emergency including where to send emergency vehicles. In his interview, Floyd
commented on the value of checklists in emergencies. He says,
we have checklists because … if I didn’t have a checklist in front of me, I’d forget
something … because if you’re … reading off the checklist, it doesn’t matter if you
get the phraseology correct, just, you know, ‘do you have any hazardous cargo on
board?’ ‘… do you have any special requests?’ … At that point you’re just reading
… and hopefully you’re writing it down legibly (Floyd, Sandy Aerodrome).
Floyd’s comment suggests that following a checklist is automatic and the language is a
natural product of the process. However, examination of the recorded simulator transcript
show that he did not ask pilots questions about hazardous cargo or special requests nor did
he pass the information to emergency services. This is partly because the aircraft in both his
exercises, had just taken off. Before take-off, the number of persons on board (POB) was
established. Since the data used for analysis was after the emergency was declared, the
transmissions about POB were not part of the corpus. Another reason for using less
technical vocabulary may have been the limitations of the simulator which meant that Floyd
had conversations “off-air”, about where he could send emergency vehicles, creating a
possible distraction. The language left out is the language the Ghaf air traffic controllers
practised. The Ghaf controllers focussed on standardising the language and consequently
used more technical language. Different training goals contributed to language differences.
4.3.2 Language choices controllers make
4.3.2.1 Use of plain language in the simulator
A keyword analysis identified greater use of plain language by the Sandy aerodrome
controller. Table 4.6 shows that the, can and you were important keywords used by him. No
51
plain language keywords were found for Ghaf aerodrome. The numbers in brackets next to
the word can show that it appeared 26 times in the Sandy corpus, makes up 1.81% of the
corpus and is a very strong keyword at 31.11 keyness. Chapter 3 identified a keyness
number of 10 or more as very strong. Table 4.6 shows that can appeared in the Ghaf corpus
once and not at all in the written corpus.
Table 4.6
4.6 Use of plain language by the Sandy aerodrome controller
Keyword Sandy Aerodrome – keyword
Appearance in keyword Reference corpus
Appearance in Ghaf Aerodrome
Appearance in written corpus
Can 26, 1.81%, 31.11 27, 0.36% 1, 0.06% 0
You 42, 2.93%, 29.51 71, 0.95% 18, 1.03% 11, 0.26%
The 90, 6.28%, 65.13 151, 2.03% 35, 2% 26, 0.61%
Due to constraints of space, 12 occurrences of the word can were analysed in comparison to
phrases with the same meaning in the Ghaf and written corpora. In Ghaf Aerodrome, can
appeared in the following phrase: We can cancel the emergency which was an instruction to
emergency vehicles. Table 4.7 shows that language use differs between Ghaf and Sandy
aerodromes.
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Table 4.7
4.7 Comparison of language used in the Sandy, Ghaf and written corpora
Sandy Aerodrome ‘can’ phrases
Meaning Ghaf Aerodrome Written Corpus
you can proceed (on
the runway)//(to)
(4)
Used to tell vehicles
to go to an
aerodrome location
Proceed to Proceed (to)//(via)
you can go to (1) go to Proceed to Proceed (to)//(via)
You can proceed as
requested (1)
Gives vehicle driver
permission to carry
out what they
requested
proceed back to
station approved
Proceed (to)//(via)
you can hold short
for the moment (1)
Stop before an
identified place e.g.
runway
Hold short of
(runway
RWYDES)//(RWYDES)
Hold short (of)
runway RWYDES
you can hold your
position (1)
Stop where you are n/a Hold position
(reason)
you can follow (1) Follow Confirm pilots
request to follow
him inside the
runway
Follow (aircraft
type)
you can land (1) Instruction to an
aircraft to land
Cleared to land Cleared to land
you can taxi (1) Used with aircraft,
move around the
aerodrome using
taxiways
Taxi for holding
point
Taxi to … via …
Taxi to … via …
Taxi to …
Taxi via …
you can expect (to
remain on the
ground) (1)
Expect Expect little delay Expect (one minute)
delay
The Sandy aerodrome controller precedes technical vocabulary with you can. For example,
in the first row of column 1, the controller says you can proceed (on/to) which is proceed to
in the Ghaf corpus (column 2) and the written corpus (column 3). The pattern you can +
technical vocabulary is repeated in all twelve uses of can by the Sandy controller. One of the
Ghaf controllers uses a largely plain language construction once in Table 4.7: where the
53
Sandy aerodrome controller says you can follow, one of the Ghaf controllers says confirm
pilot’s request to follow him inside the runway. This statement combines technical
vocabulary (confirm, request, runway) with plain language.
4.3.2.3 Attitudes towards the use of standard phraseology
The interview data revealed that controllers have different attitudes about the use of
standard phraseology. Comments from two controllers show how they approach
communication when standard phraseology is not sufficient,
standard RT [radiotelephony] doesn’t cover all the situations so there are always
some kind of deviations from the standard RT because the situation requires to act
a little bit more differently (Oliver).
I learned on the job so I become … Like for one year I spend 1 year just for training
this phraseology, how to speak, how to understand, how to get down some of
these things, until … I create my own procedure. My own words. I can use it, but
within the standard. So I have to start with the standard, but using my own words
(Mansour).
These controllers treat standard phraseology as a language which is adapted to different
situations.
This view contrasts with Floyd who sees standard phraseology as a set of phrases to be used
in certain circumstances beyond which plain language or general English is used. He states,
There’s no phraseology built for hydraulic failure and you know, the pilot needing
an odd request … there’s no set phraseology (Floyd).
in other situations um yeah definitely no phraseology, just get the information
you need, talk to the pilot like a human being right (Floyd).
Floyd reiterated the point that you should ‘just talk to the pilot’ four more times in his
interview. The implication is that plain or general English is used when there is no standard
phraseology.
54
4.3.2.4 Beliefs about language use and training for emergencies
The controllers’ held differing beliefs about language training for, and language use in,
emergencies. Two controllers shared similar beliefs about language use. They stated that
controllers should be silent during emergencies since the pilot is busy in the cockpit and
should not be disturbed. They also felt that the language could not be practised since there
is no standard phraseology and plain language is used. Their views are summed up in the
following quotes,
during emergencies, more plain language [is] used. There’s no standard (Axel).
anything that’s non-standard, can’t teach that (Floyd).
Axel and Floyd thought that a controller who had achieved ICAO English language
proficiency Level 4 would know what to say in an emergency. While the remaining seven
controllers agreed that English language proficiency is necessary, they had a different
opinion about training in that they believed that language training for emergencies would
be useful. Shaikha sums up,
[Training] will help us in our realistic work so we can understand pilots from
different nationalities (Shaikha).
Language training for emergencies gives trainees a chance to consider the language they
might need. As Mansour puts it,
Uum sometimes in the simulator they create something like an abnormal, then
you have to create your language, you know, you have to like digging inside
your mind to put the words (Mansour).
This group of controllers felt that language training would give them an opportunity to
identify language they might use in the workplace before they needed it.
4.3.2.5 How the simulator differs from the workplace
The controllers stated that the simulator is quite different to their work in real life. They
identified differences including the slower pace of the simulator; and that simulator pilots
have good standard phraseology and English language proficiency. Since the simulator
pilots’ language skill is high, the controllers know what the pilots will say and rarely need to
clarify meaning. The simulator represents a best-case scenario in which all participants have
55
the language skills for the task. The next section examines the environmental factors that
affect language use in air traffic control.
4.3.3 Environmental factors that influence the use of technical vocabulary in the workplace
4.3.3.1 Multicultural context and miscommunication
Pilots and controllers in the UAE come from diverse backgrounds and have different
approaches to communication. At Ghaf aerodrome and both civil airports, pilots came from
countries such as: Russia, Egypt, Australia, France, America, China, India and England.
Controllers gave three reasons for miscommunication. The first reason was the low
language ability of some pilots. Some Arabic speaking controllers said they resorted to their
native language for safety reasons in some instances. The second reason was difficulty in
understanding the many different accents of the pilots. While there is no doubt that these
factors have a significant impact on miscommunication (discussed in Section 4.3.3.3), they
are beyond the scope of this research and will not be investigated. The final reason was the
differences in the language use of native English speakers (NES) and non-native English
speakers (NNES) and this point is explained more below.
4.3.3.2 Native English speaker contributions to miscommunication
In the interviews, differences in language use between native English speakers (NES) and
non-native English speakers (NNES) were considered important. Three themes presented
themselves in the data. First, the controllers thought that NNES use more standard
phraseology for three reasons. They use a narrower range of words, more phraseology and
are better at radio communication than NES. They explain,
non-English speakers tend to stick to specific words and phrases (Nelson).
When it comes to the non-native I would say that … they might be more keener to
stick to the standard RT [radiotelephony] (Oliver).
my experience is that … [if you have] English as second language you speak it
better on the radio compared to mother tongues (Axel).
Second, in contrast to non-native speakers, native English speakers use more slang, complex
grammar, different vocabulary, speak quickly and use more general/plain English. They say,
56
Um and one of the problems that I see native English speakers having is they tend
to fall back on slang and words that are not … phraseology (Nelson).
that’s the danger I think … when a native speaker uses too complex … sentence
structures (Oliver).
so they use their own like aviation English back in Australia, so when they come
here, they say the words they use … which … we don’t understand (Mohammed).
Some of them [speak faster] yes. Usually because they are flying, they don’t have
time (Alia).
The native speaker, they speak in a … mother tongue with a dialect (Axel).
They’ve been using more plain language and less of the standard phraseology
(Oliver).
Third, the greater use of plain language causes miscomprehension. For example, Nelson and
Oliver say,
if I’m using a slang word … and English is their second language they may not
understand it or they may take it as something … totally different because in
English the same word could have two different meanings (Nelson).
when the native speaker he uses really complex language ah the comprehension
might be off (Oliver).
In summary, the findings suggest that NNES tend to use more technical language while NES
are more likely to use complex or wordy language. These differences in language use can
lead to miscommunication. When this happens, the controllers need to clarify meaning to
resolve the situation quickly.
4.3.3.3 Clarification of meaning to resolve miscommunication
Clarification of meaning is common in these workplaces. Two themes emerged from the
interviews about how meaning is clarified. First, the controllers need to ask the pilots to
repeat their request, as Oliver, Mohammed, Alia and Mariam point out,
I sometimes mirror back the request, can you confirm that I understand it correctly? …
(Oliver).
57
You should ask him again, say again what you mean (Mohammed).
Even back with answer that you explain ‘I understand like blah blah blah’ this is what
you mean? (Alia).
I don’t know what he want … and I have to ask him again and again (Mariam).
Second, they ask their colleagues to clarify meaning by asking them what the pilot said, as
four controllers explain,
[new air traffic controllers from the UK] sitting in the seat getting trained and there’s a
lot of … ‘what’d he say?’ ‘what’s he asking?’ (Floyd).
Ask maybe some of our colleagues … what does he mean? So they like explaining.
Definitely it’s hard … you know (Mohammed).
So it’s hard work, but if I stuck on something it will not work. Someone have to take
over to understand what they want (Mariam).
sometimes we have to ask a native speaker English just to tell me what exactly that
person has said (Mansour).
In summary, clarification of meaning is sought by asking the pilot to repeat their request or
by asking a colleague to explain what the pilot said. The multilingual element of the UAE
workplace makes communication challenging in a fast-paced environment and clarification
of meaning is a common occurrence.
Miscommunication may be less of an issue in monolingual environments. Oliver comes from
Estonia where most of the pilots and controllers speak the same first language. He
mentioned the contrast of this environment to his workplace in the UAE,
we have the same meaning for that word [so] that we understand each other. Let’s
say when I work back home, … there is really kind of standard way to use the RT
[radiotelephony] or the plain English because the patterns are the same every time
(Oliver).
In other words, the pilots and controllers have the same language background which makes
it easier to understand each other. Many of the communication issues mentioned in this
section are a product of the diverse backgrounds of pilots and controllers. This diversity
58
means they come with different beliefs about the use of technical language in
radiotelephony.
4.4 Summary of results
This chapter has presented the findings of this research. It began with a description of the
technical vocabulary contained in the Aviation Radiotelephony Word and Number List. The
coverage of technical vocabulary in the spoken corpora was established next. Then, the
three factors which influence the extent to which technical vocabulary is used by different
controllers was explored. The first factor was the nature and purpose of simulator training
for emergencies. The second factor was the language choices controllers make based on
their attitude towards the use of standard phraseology. Controllers also had differing beliefs
about the language used in emergencies, as well as language training for emergencies. The
simulator provides an environment quite different from the workplace, so the third factor
was the workplace environment in the UAE. Controllers and pilots come from a variety of
backgrounds with differing language use which causes miscommunication. Native English
speakers contribute to miscommunication when they use difficult vocabulary or complex
grammar. Clarification for meaning is a frequent occurrence in the workplace. The
significance of these findings is examined in Chapter 5.
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Chapter 5 Discussion
This chapter first examines technical vocabulary coverage compared to other professions
and shows that radiotelephony language in the simulator is highly specialised. The high
coverage confirms that technical vocabulary is an essential component of this language.
Second, the Aviation Radiotelephony Word and Number List is applied to two language
extracts to show how plain language is used in communication. Finally, a Model of
Controllers’ Beliefs and Language/Training Outcomes in Aviation Radiotelephony is
presented. This model summarises the quantitative and qualitative data from this study to
show how controller beliefs affect their language use and underpin beliefs about training.
5.1 Technical vocabulary coverage compared to other professions
Technical vocabulary is a significant proportion of the language used in aviation
radiotelephony in emergencies. Chapter 4 showed that coverage was 70.52% and 51.61% of
the spoken corpora for Ghaf and Sandy aerodromes respectively. These figures are
considerably higher than other professions. The aviation corpora contain five to seven times
as much technical vocabulary as the four trades examined in Chapter 2 which confirms that
radiotelephony language is highly coded and specialised (Estival & Farris, 2016).
Chapter 2 showed that written corpora contain more technical vocabulary than spoken
corpora in previous studies. In the case of each of the trades, the written corpora included
more than three times the technical vocabulary of the related spoken corpora. In this
aviation study, every second word in the Sandy aerodrome corpus and two words out three
for Ghaf aerodrome are technical, yet these figures occur in spoken corpora. This high
technical vocabulary coverage explains why radiotelephony communication is unintelligible
to native English speakers in a way that other specialist spoken discourse, such as business
English, is not (Estival, 2016).
The technical vocabulary coverage is high in aviation radiotelephony because
communication is focussed only on the problem to be solved i.e. the emergency. Further,
the emergencies in both aerodromes were straightforward with all traffic needing to, and
being able to, land normally. Communication with the emergency aircraft was limited to
landing clearances, requests for information to be passed to emergency services and
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requests for the pilot’s intention once they landed. Much of this communication was routine
in nature and achieved using technical vocabulary and standard, subsidiary or local
phraseology. The best-case scenario nature of the simulator may also have increased the
coverage of technical vocabulary since all participants used correct standard phraseology.
The repetition of routine manoeuvres, such as several non-emergency aircraft carrying out
low passes over the runway, in the Ghaf corpus, resulted in a high proportion of routine
communication.
5.2 Using the Aviation Radiotelephony Word and Number List to examine the role of plain
language
Technical vocabulary is essential in radiotelephony communication. This section examines
the elements of the technical language of aviation radiotelephony by focussing on two
language extracts. The first extract is taken from the Ghaf corpus in this study and contains a
high proportion of technical vocabulary. The second extract is from an ICAO (2010)
document where it is presented as an example of plain language in radiotelephony
communication. This extract was chosen to provide a contrast to the relatively
straightforward situation contained in the simulator extract and to more closely examine
the nature of plain language use in a highly complex situation.
In both extracts, MWUs, technical vocabulary and plain language are used to solve a
problem. In the first example, the problem is that an aircraft needs to land because an
engine has stopped working. In the second, the pilot needs information to make an
informed decision about a diversion which may save a passenger’s life. The Aviation
Radiotelephony Word And Number List was applied to these extracts using the Heatley et al.
(2002) Range programme to identify technical vocabulary. The original extracts are shown
below, but for analysis, each of the extracts was coded and multiword units were combined.
Consequently, the number of types in the analysis differs from what is presented here. The
technical vocabulary is in bold in each extract. Underlined phrases are those in which
technical vocabulary is adapted with the addition of plain language. Phrases which are not
underlined consist of mainly plain language. The callsigns have been changed in the Ghaf
extract (Extract 5.1) to retain anonymity of the workplace.
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5.2.1 An emergency in the simulator
The first extract includes high technical vocabulary coverage and shows how important this
vocabulary is to radiotelephony communication in this emergency. Extract 5.1 is divided into
3 columns. The first column identifies the purpose of the communication and the second
identifies the speaker e.g. in Turn 1, the pilot informs the air traffic controller about an
emergency. The transmission is contained in column 3. Extract 5.1 contains 71 types, 44
technical vocabulary items and 61.97% coverage. MWUs are used in Lines 1 – 8 and 10 - 12
in this emergency. For example, runway 27, continue approach, report short final are all
MWUs which relate to routine Standard Operating Procedures (SOPs) (Mitsutomi & O'Brien,
2003). The communication follows the structure of pilot initial call, controller response and
pilot readback found in routine radiotelephony communication (Estival, 2016) in Lines 1 – 3.
Controller instruction and pilot readback occurs again in Lines 6-7, and 11-12. Lines 4 and 5
also represent a routine exchange, but in this case, the controller requests information (4)
and the pilot provides the information (informs) in Line 5. Even though this dialogue is about
an emergency, the first twelve lines contain routine communication composed almost
entirely of technical vocabulary. Essential meaning is communicated through multiword
units and technical vocabulary.
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Extract 5.1
5.1 Extract from Ghaf corpus: Engine flameout emergency
Purpose Turn no.
and speaker Dialogue
Inform 1 Pilot Tower G-ABCD Mayday mayday mayday engine flame out requesting straight-in landing for runway 27
Give instructions
2 Tower (TWR) controller
G-ABCD. Emergency acknowledged. runway 27. Continue approach. Report short final.
Read back instruction
3 Pilot Report short final. G-ABCD.
Request information
4 TWR Controller
G-ABCD when able request total POB fuel on board and ah any hazard cargo
Inform 5 Pilot Ah 1 POB 2 hours fuel endurance negative hazard cargo G-ABCD
Give instruction
Line 6 TWR controller
G-ABCD Roger. Continue approach
Read back Line 7 Pilot Continue approach. G-ABCD
Request intention
8 TWR controller
Request intention after landing
State intention
9 Pilot I will advise once landed. G-ABCD
Acknowledge 10 TWR controller
Roger
Gives instruction
11 TWR controller
G-ABCD runway 27 check gear down. Cleared to land
Read back 12 Pilot Cleared to land. G-ABCD
Request assistance needed
13 Ground (GND) controller
Do you require an assist?
Inform 14 Pilot Ah that’s affirm requesting tow. We won’t be able to move G-ABCD. We won’t be able to taxi
Request intentions
15 GND controller
Copy. Confirm are you going to vacate runway then stop for towing?
State intentions
16 Pilot Ah negative. We will be stopping on the runway. G-ABCD
Give instruction
17 GND controller
G-ABCD. Copy. And advise when the traffic totally stop
Acknowledge 18 Pilot G-ABCD
Inform 19 Pilot We are stop on the runway
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Plain language is used with technical vocabulary to clarify a deviation from standard
operating procedures. For example, the question in Turn 15: are you going to vacate
runway then stop for towing? uses plain language to ask about the pilot’s intentions, but
the essential meaning is conveyed using technical vocabulary (in bold). The standard
procedure is for the pilot to exit the runway and taxi to a parking spot. Turn 15 represents a
deviation from the standard procedure clarified with plain language. MWUs are used, along
with technical vocabulary with plain language to clarify meaning or ‘adapt the phraseology’
as the controllers in this study stated in interviews. Plain language is used with technical
vocabulary, by the simulator pilot in Turns 9 and 16 to state intentions; and in 14 and 19 to
inform. It is used by the controller in Turn 13 to ask what assistance the pilot needs, in Turn
15 to request intentions and in Turn 17 to give an instruction. In each of these turns, there is
no standard phraseology available and each phrase represents adapted technical
vocabulary.
5.2.2 An emergency involving a critically ill patient
Technical vocabulary is essential even when plain language makes up a greater proportion
of communication. A high proportion of plain language can disguise the fact that a request is
technical. In contrast to the analysis above, this section examines an extract which is mostly
plain language and differs from the previous one because it is a complex emergency.
Although M. Barry, an air traffic control instructor, (personal communication, August 18,
2020) identified this example as an unusual situation, Eurocontrol (2019) states that an
event is an emergency when the safety of an aircraft or someone in the aircraft is
endangered for any reason. Since the patient in this example is critically ill, the extract is
treated as in an emergency here. Extract 5.2 is taken from ICAO (2010) and is reproduced
because it represents language use not found in the corpora in this study, but illustrates
how the technical vocabulary word and number list can be applied to clarify the role of
technical vocabulary and plain language. The extract contains 82 types of which 17 are
technical vocabulary items with 20.73% coverage. Plain language is again used to clarify
technical vocabulary, even though the request is more complex than the previous example.
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Extract 5.2
5.2 Extract of a military pilot requesting diversion possibilities: Medical emergency
Number & Purpose Dialogue
Explanation (A): I have, I have a request (1). Our patient is a victim of an automobile accident. Requesting immediate (2) orthopaedic surgery for her severe condition.
Request
(B): Do you know from our route of flight, as per our flight plan of any fields in (name of country) in the event of … that we may divert into, where medical crews can meet the aircraft,
Explanation (C): with transportation by ambulance and immediate transport to surgery?
Request (D): We would like a request (3), of names of fields along our route of flight shortest distance from our positions along our continued route
(E): if you could please ask;
Clarification (F): we are not requesting a diversion (4) at this time.
Condition (G): However if it is approved by our controlling air force we’ll then be requesting this diversion (5).
(H): How do you copy sir?
This extract is from ICAO (2010, p. 3.5). It is a single transmission made by a pilot to an air traffic controller. It has been divided into parts here to simplify the discussion.
There are four elements to this communication. The first element is an explanation about
why the pilot would like information for a possible diversion contained in parts A and C. The
pilot explains why they might need a deviation from standard operating procedures. In this
explanation, the line between adapted technical vocabulary and plain language is less clear
than in Extract 5.1. The word to is highlighted as a technical word but is used in its general
sense (transport to surgery). The word request is used in its general sense in (1), but in (2)
Requesting immediate uses the structure of standard phraseology. Otherwise, the
explanation is plain language which is limited to the problem at hand and clarifies why the
diversion might be needed and what would be required should it happen i.e. transport to
surgery. However, the words automobile and orthopaedic raise questions about the scope
of the plain language used here. Plain language needs to be limited to the vocabulary which
would be understood by aviation personnel who hold ICAO Level 4 language proficiency. In
65
this request, the controller should understand that the patient needs immediate surgery
and the kind of surgery required in order to fulfil the request for diversion information. In
the language proficiency requirement (LPR) rating scale, Level 4 vocabulary is defined as:
Vocabulary range and accuracy are usually sufficient to communicate effectively on
common, concrete, and work-related topics (1). Can often paraphrase successfully
when lacking vocabulary in unusual or unexpected circumstances (2) (ICAO, 2018,
p. A.1 numbers added).
The air traffic controller needs to understand the words automobile and orthopaedic. These
words fall outside the first part of the vocabulary LPR (1) above since they are not common,
concrete or work-related topics. It also seems that the burden for paraphrasing (part (2) of
the LPR) in this case falls on the pilot. These words could be simplified by replacing them
with car and a description of the medical problem e.g. broken back/leg. The explanation in
(A) and (C) is to say why the pilot wants a deviation from standard operating procedures.
The second element is a request for information about a diversion. The information
required is a list of aerodromes near the pilot’s intended flightpath, with an appropriate
hospital nearby in parts B and D. Further, the request includes the MWUs route of flight,
flight plan, and How do you copy?. It also includes adapted technical vocabulary (the
underlined phrases) to clarify the technical request and plain language for politeness (Lopez,
Condamines, & Josselin-Leray, 2013; Moder, 2013) in D we would like. Further, it is a
technical request since the controller must know how to find this information. Pilots in civil
aviation would ask their airlines to provide the information and their contact with air traffic
control would be to ask for a diversion. In this case, a military pilot has asked for the
information because it is not available through the air force but the controller could request
the information from search and rescue in most area control centres (M. Barry, personal
communication, August 18, 2020).
The third element is clarification about the request for a diversion in parts F and G. The pilot
clarifies that this is not a request for a diversion, as such a request is conditional upon
approval by the air force. To get approval, the pilot will need to follow procedures which
would also apply to a decision to divert. Further, the condition is technical since an aircraft
cannot simply divert to another airport as a diversion must be coordinated with air traffic
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control in other centres. The airports chosen must account for the type of aircraft and be
able to accommodate it. The information requested is technical information related to
standard operating procedures for diversions, for an appropriate airport and for approval
from the air force. The fourth element (E) is a polite phrase recognising the extra workload
this request created for the controller (Moder, 2013). It differs from the rest of the
transmission because the purpose is to maintain a relationship with the controller (Lopez,
Condamines, & Josselin-Leray, 2013; Moder, 2013). While the language in (E) is general
English, it serves a narrow and defined purpose in the communication.
Finally, Extract 5.2 is syntactically complex. It is an example of spontaneous language use by
a native English speaker (Estival & Molesworth, 2009) which would cause difficulties for
aviation personnel with ICAO Level 4 language proficiency. Estival and Molesworth (2009)
identify this kind of language use as a reason why highly proficient English speakers should
be taught to simplify their language and speak slowly.
5.2.3 Plain language in aviation radiotelephony
In contrast to the complexity of plain language presented in Chapter 2, this study suggests
that plain language may be a simplified form of English. ICAO (2007, 2010, 2016a) states
that plain language should be clear, concise and unambiguous. As stated in Chapter 2, it is
‘constrained by the functions and topics (aviation and non-aviation) that are required by
aeronautical radiotelephony communications, as well as by specific safety-critical
requirements’ (ICAO, 2010, p. 3.5). This study suggests it could also be further limited in two
ways. First, it is confined to the language needed to clarify and solve the problem at hand.
Second, it should be limited for understanding by all users. All aviation personnel are
required to meet the ICAO Level 4 language proficiency standard, so vocabulary should not
exceed that requirement. Plain language may include the grammar found in ICAO standard
phraseology such as requesting immediate but the spontaneous language use found in
Extract 5.2 may be beyond ICAO Level 4 language users. Prado (2015) (written in
Portuguese) cited in Silva and Tosquil Lucks (2020) showed that the grammatical structures
in radiotelephony followed the principles of simplicity and clarity required by ICAO. Plain
language should use simplified vocabulary and structures to clarify technical problems or
deviations from standard operating procedures. It is combined with technical vocabulary
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and the amount of plain language used depends on the complexity of the situation rather
than what kind of situation it is. A straightforward emergency, such as those examined in
this research, require very little plain language (Section 5.2.1). A more complex situation
requires more plain language (Section 5.2.2). Ultimately, the assumption that more plain
language is used in emergencies (Read & Knoch, 2009) was not supported in this study.
Rather, the use of plain language relates to particular situations.
5.3 Miscommunication and controllers’ beliefs about standard phraseology
This section explores how variation in beliefs about standard phraseology can cause
miscommunication in the workplace. It presents a model of controllers’ beliefs about
language use in general and in emergencies and the outcomes of those beliefs. The model in
Figure 5.1 was developed by combining information from the quantitative and qualitative
data. This section gives an overview of the model, then explores the beliefs and consequent
outcomes. One belief included in the model was held by all controllers (A), that aviation
personnel should have achieved the minimum language proficiency of Level 4 required by
ICAO. The model is centred around three belief categories identified in interviews: the role
that standard phraseology plays in radiotelephony (B); what constitutes the language used
during emergencies (C); and the benefit or otherwise of language training for emergencies
(D). The outcomes are organised around two areas. The first is language use (E) in which the
composition of the language identified by the controllers in interviews and found in
quantitative analysis is summarised. The second is the purpose of emergency training (F) for
each of the aerodromes in this study.
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Figure 5.1
5.1 A Model of Controllers' Beliefs and Language/Training outcomes in aviation radiotelephony
Beliefs
Meet ICAO minimum levels for English (A)
Basis for radiotelephony (1) (B) Standard phraseology
Limited set of circumstances (7)
Standard phraseology is necessary (2)
(C) Language use in emergencies
Use more plain language (8)
Must be silent (9)
Beneficial (3)
Practise aids successful outcomes (4)
(D) Language training for emergencies
No phraseology, so can’t train (10)
Language proficiency is enough (11)
Outcomes
More technical vocabulary (5)
(E) Language use
More plain language (12)
Strategies for cooperation (13) May use complex grammar; slang
(14)
Language (6) (F) Emergency
training to practise
Logistics (15)
Controllers on the left-hand side of the model view standard phraseology as a technical
language which forms the basis of radiotelephony communication (1). These controllers
treat the language for radiotelephony as a standalone language in which standard
phraseology is frequently adapted, using plain language, to circumstances as they arise
(Section 5.2.2). Controllers talked about adapting standard phraseology, but it appears they
mean adapting the technical vocabulary of standard phraseology to different circumstances.
A similar finding was made by Rees (2013) who showed pilots and controllers frequently
need to adapt their language in routine situations. The next belief about language use in
emergencies is that standard phraseology is necessary (2) and should be used as much as
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possible. The final beliefs relate to language training for emergencies. From this point of
view, language training for emergencies is beneficial (3) because it allows controllers to
practise (4) what they will say before an emergency happens and helps to reduce panic in a
real emergency. The outcomes of these four beliefs are that controllers are more likely to
use more technical vocabulary (5) and the focus of emergency training can be language (6).
On the other hand, the first belief on the righthand side is that standard phraseology is a
series of phrases for a finite set of circumstances (7) beyond which it serves no purpose and
plain language is used. In terms of emergencies, these controllers believe that more plain
language is used (8) and that controllers need to be silent (9) since the pilot is busy in the
cockpit and should not be distracted. These controllers believe that language training for
emergencies is not possible since there is no phraseology for use in emergencies (10). Also,
every emergency is different, so if controllers have sufficient English language proficiency,
then they can successfully deal with emergencies (11). The outcomes of these beliefs are,
first that more plain language is used (12). Second, that strategies for cooperation are used
(13). Keyword analysis showed Floyd used you can with standard phraseology as ‘a strategy
to accomplish cooperative actions effectively’ (13) through mitigation (Moder, 2013, p. 259)
or as Lopez, Condamines and Josselin-Leray (2013) explain, to courteously convey the
authority contained in instructions. Third, language use is more likely to include complex
grammar and slang (14). The final outcome is that the purpose of training is logistics (15).
The controllers’ language use is not divided according to language background, but
according to their beliefs about the role of standard phraseology. Interview data suggests
that NNES are more likely to demonstrate the language use (D) shown on the left-hand side
(6) and NES are more likely to display outcomes (12) – (14) on the right. Two controllers did
follow this pattern. Mansour was one of the NNES controllers whose training session was
recorded with language and training outcomes (5) and (6). During interviews he expressed
beliefs (1) - (4) on the left-hand side. Floyd’s beliefs were in stark contrast to those held by
Mansour. Floyd expressed all the beliefs on the righthand side i.e. (7) - (11) with outcomes
(12), (13) and (15). Mansour and Floyd’s beliefs and outcomes were divergent and represent
two distinct paradigms, so provide the basis for the model. Other than Floyd and Mansour,
only one other NNES controller, Oliver, held beliefs (1) – (4) with (5 self-reported) as the
outcome. The remaining controllers did not all fit neatly into the left-hand side or righthand
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side of the model. For example, Nelson is a NES, but believes in (1) – (4) with training at (6),
and (5) for language use (self-reported). He advocated for greater standardisation of
language use in emergencies and generally for all situations. Further, he felt that standard
phraseology needed to be emphasised and tested in ab initio training. Axel is a NNES who
believes in (1) on the left-hand side, but (8) - (11) about emergencies on the righthand side.
The outcomes for him were (15) for training on the righthand side, and (5) for language use
(self-reported).
This variation in beliefs can help explain miscommunication. ICAO (2010) gives the example:
‘Can we keep high speed?’, and explains that ‘there is no ICAO phraseology for this pilot’s
request for permission’ (p. 3.6) suggesting that no phraseology means plain language must
be used instead. Controllers or pilots who, instead, see standard phraseology as the basis of
a technical language might say ‘Request maintain speed’ which applies (adapts) the
principles and vocabulary of standard phraseology to circumstances for which there is no
phraseology (1). The bolded words request, maintain and speed are technical words in the
Aviation Radiotelephony Word and Number List, so the outcome is greater use of technical
vocabulary (5). Conversely, ‘Can we keep high speed?’ matches language use in (12) and
(13) and follows from the assumption that plain language is used when there is no standard
phraseology (7). This short phrase has resulted in very different language use and technical
vocabulary coverage (100% versus 20%), depending on the beliefs of a controller.
The assumption that a minimum level of language proficiency by NNES aviation personnel is
enough to successfully resolve emergencies (J. Read in Hirch, 2020; ICAO, 2010; Trippe &
Baese-Berk, 2019), which is a belief also held by some controllers (8) and (11), did not hold
up in this study. This assumption is based on a shared language background (Read & Knoch,
2009; Trippe & Baese-Berk, 2019) rather than a multi-lingual environment like the UAE. The
purpose of the Ghaf controllers’ simulator training was to address their handling of
emergencies which led to confusion. All the controllers had achieved English language
proficiency of ICAO Level 4 (the minimum level required for a licensed air traffic controller
by ICAO (2018), but their resolution of emergencies varied. Further, in the workplace, the
differing language backgrounds of controllers and pilots led to frequent misunderstandings
and clarification of meaning (Field, 2020). As noted in Chapter 4, this miscommunication
contrasted with Oliver’s experience in Estonia where controllers and pilots had a shared
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understanding of the meaning of words. It appears that the assumptions that underpin ICAO
documentation may be flawed.
In summary, the proportion of technical vocabulary used by controllers could be measured
and showed differences in its use. Language use may relate more to underlying beliefs
about standard phraseology than to NES or NNES language background, although outcomes
are more likely to be on the left-hand side for NNES and on the right for NES. Estival and
Molesworth (2009) also make this point, suggesting that differences in language background
do not influence how well pilots understand air traffic controllers. Rather, the language
controllers use is key to understanding. The beliefs identified by the controllers also
influence the purpose of emergency training they undergo (language or logistics), which
perpetuates their language use and the disparities identified in outcomes, more technical
vocabulary or more plain language. One reason for miscommunication in the workplace
could be because controllers have differing understandings about the importance of
standard phraseology in aviation and how or when plain language should be used, which
results in different coverage of technical vocabulary. The division in beliefs shown in Figure
5.1 mirrors the division of assumptions and definitions contained in ICAO documentation.
5.4 Summary of discussion
This chapter identified aviation radiotelephony as a highly technical language in comparison
to other professions. It examined the role of plain language and found that it is used to
clarify and solve problems. For clear communication, which is understood by all users, plain
language should be a simplified version of English. The proportion of plain language
required depends on the complexity of the situation rather than the nature of the situation
i.e. emergencies do not necessarily result in greater use of plain language as previously
assumed.
Differences in the use of technical vocabulary can result in miscommunication for which
clarification of meaning (and plain language) is required. Controllers’ beliefs about the role
of standard phraseology, rather than their language background, influence the extent to
which controllers use technical vocabulary. Beliefs about standard phraseology underpin
training and perpetuate differences in language use.
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What is clear from this discussion, is that aviation radiotelephony communication uses a
highly specialised language which needs to be learned and practised by all users.
Implications for testing and training are presented in Chapter 6.
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Chapter 6 Conclusion
This study set out to identify the language trainee air traffic controllers need to learn and
use in emergency training in the simulator. However, once I began to delve into the
language my students would need, it became clear that my grasp of the technical language
was insufficient to appraise the data I had collected. Further, the small corpora meant I
needed to retain all the language collected for analysis, so examining only the plain
language would have left very little data. Finally, I could not identify where standard
phraseology finished and plain language began. The study was re-designed to identify the
technical vocabulary, so that the extent to which it was used (rather than the extent of
standard phraseology and plain language) could be established. The findings provided useful
information for establishing training and testing needs in the UAE environment. This chapter
outlines the focus and contribution of this study, implications for training and testing,
limitations, future research and concluding remarks.
6.1 Focus and contribution of this study
An Aviation Radiotelephony Technical Word and Number List was developed. The list
clarified the nature of technical vocabulary in radiotelephony in simulator emergencies. It
was used to establish the technical vocabulary coverage in spoken corpora which was high
compared to spoken and written corpora in other fields. This confirmed that a highly
technical language is used in radiotelephony communication and it must be learned by all
users. The list also helped clarify the nature of plain language required in a multilingual
environment such as the UAE. Plain language should be simplified English. It is combined
with technical vocabulary to clarify and solve technical problems related to standard
operating procedures. The extent to which plain language is used is according to the
complexity of the issue to be resolved rather than to the type of problem. A simple
emergency may be resolved using mostly technical language while a more complex one may
require more plain language. In either case, radiotelephony is focussed on solving the
problem at hand.
Finally, a Model of Controller Beliefs and Outcomes was presented. This model summarised
the quantitative and qualitative data in this study to explain the variation in language use
found in the corpora and identified in interviews. The most profound diversion in beliefs
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was on the one hand, controllers who thought that standard phraseology was a standalone
language to be adapted to different circumstances. According to the model, these
controllers use more technical vocabulary. Conversely, other controllers believe that
standard phraseology is for a limited set of circumstances. These controllers will use less
technical vocabulary, more plain language and may use slang and complex grammar. These
beliefs also underpin training, so training is likely to perpetuate the divergence in language
use identified in this study.
6.2 Implications for training
This study shows that language training would be useful to aid standardisation of language
use in order to reduce divergent language outcomes. Language practise is useful since it
means that a controller has already practised the language for a situation before it arises. A
common belief in air traffic control is that it is not possible to provide language training (or
testing) for every situation (Farris, 2016a). However, language training provides trainees
with tools they can adapt to situations they encounter. This section begins with training
needs for ab initio controllers and finishes with experienced controllers from different
language backgrounds.
Ab initio controllers would benefit from language training related specifically to
radiotelephony regardless of language background. The training would complement
simulator training and happen in the classroom to reduce the cognitive load of learning
language at the same time as learning how to direct traffic (Drayton & Kelly, 2019). The
Aviation Radiotelephony Word and Number List helps identify words or numbers that are
difficult to learn or have dual meanings. It also identifies numbers that could cause
confusion, not only for the controllers, but for pilots. Hoffman (2020) gives an example of a
trainee pilot who mistook a wind direction for a heading (compass direction) and had to be
re-directed away from mountains. Air traffic control instructors highlight areas of confusion
such as this, but extra practise aids learning and retention. Language extracts like Extract 5.1
from the corpus can be used to provide examples of simulator emergency language use in a
similar fashion to Riddiford and Newton (2010) who used authentic workplace dialogues to
train learners for communication at work. The corpus can also be used as a basis for task-
based language learning which makes the training as close to real interactions as possible
(Willis & Willis, 2007).
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Experienced controllers would also benefit from language training. For them, the Model of
Controller Beliefs and Outcomes provides a useful starting point to re-consider how they use
language in radiotelephony. Many authors have suggested that native English speakers
should be encouraged to modify their language by paraphrasing based on standard
phraseology to accommodate less proficient speakers (Clark, 2017; Moder, 2013; Moder &
Halleck, 2009). This language modification would mean that controllers base their language
on technical vocabulary or standard phraseology as described by the controllers in this
study. That is, treating radiotelephony as a language rather than a division into two arbitrary
but difficult-to-distinguish parts (standard phraseology and plain language). Training to
achieve a more standardised approach to language would look at scenarios where a high
proportion of plain language was used to identify how (if) it could be replaced with technical
vocabulary to produce clear and unambiguous communication (GCAA, 2018; ICAO, 2007,
2010, 2016a, 2016b). The scenarios Kim and Elder (2009) and Bieswanger (2013) provide,
where wordy language is used, are good examples of language exchanges for this training.
Aviation professionals from different backgrounds (native and non-native English speakers)
would enrich the discussion in training of this nature. The training would involve practice of
scenarios where problem-solving and clarification is needed. For highly proficient English
speakers, this practice involves simplifying their language to be understood by less
proficient speakers (Clark, 2017; Kim & Elder, 2009; Moder & Halleck, 2009). For others, the
purpose of practice is to transition between plain language and technical vocabulary for
clarification. This a skill that pilots and controllers identified as essential (Knoch, 2014).
6.3 Implications for testing
Testing ab initio controllers on radiotelephony language is beneficial. The Aviation
Radiotelephony Technical Word and Number List provides a basis for diagnostic testing of
ab initio controllers’ knowledge of the technical vocabulary for aviation radiotelephony. A
diagnostic test before they start simulator training would be useful to identify areas of
weakness. At the end of their simulator training, ab initio controllers could be required to sit
a radiotelephony test of their language skills in emergencies. This test could be based on
corpus examples and the word and number list. However, a larger corpus is required for a
more representative language sample. Nevertheless, testing would give trainees and
instructors useful feedback about their ability with the radiotelephony language.
76
Testing is essential when language backgrounds differ. Some authors have advocated for
language tests and language proficiency requirements which reflect the language controllers
(and pilots) use in the workplace (Elder et al., 2017; Kim, 2018; Kim & Elder, 2009, 2015). Dr
John Read in Hirch (2020) worked with air traffic controllers to develop a test of
radiotelephony language, however he was unable to verify its success. The use of such tests
is not widespread and the call for technical language tests is not new. Almost 20 years ago,
Verhaegen (2001) argued that aviation personnel should have a proven ability in standard
phraseology, implying that they should be tested. Research shows that ability in general
English does not translate to success using aviation radiotelephony language (Moder &
Halleck, 2009; Trippe, 2018). This current study highlights the highly technical nature of
aviation radiotelephony and suggests that it is a reason why a good grasp of general English
does not equate to success in radio communication. A test of this highly specialised
language is required, for safety reasons, to ensure aviation personnel have the requisite
technical knowledge (Kim, 2018) and can use language which could be understood by an
ICAO Level 4 speaker (Clark, 2017; Kim & Elder, 2009, 2015; Moder & Halleck, 2009)
especially in a multilingual environment like the UAE.
6.4 Limitations
This research did not set out to identify technical vocabulary, so the corpora are smaller
than would normally be used for vocabulary research (Nation & Webb, 2011). Further, the
small size of this study means the findings are not generalisable. However, small corpora
can provide useful information (Gavioli, 2005) which is potentially richer than information
from a larger corpus because the researcher is familiar with the context and participants
(Vaughan & Clancy, 2013). The addition of manual tags to a small corpus allows the
generation of quantitative results (Vaughan & Clancy, 2013). Finally, wordlists can provide
quantitative data to make inferences when it is enriched with qualitative information
(Vaughan & Clancy, 2013). These advantages of small corpus work enhanced the findings in
this study. Second, limiting the focus to emergencies only, meant that some of the recorded
data was not included in the sample for analysis. In one case, this meant that technical
language which occurred in the written corpus was not part of the spoken corpus because it
occurred before the emergency began. Third, the research was carried out in a simulator
and not an air traffic control workplace. Consequently, the clarification of meaning
77
identified as important by the controllers is not captured in the corpora. In addition, the
coverage of technical vocabulary identified in this study may not represent real-life
communication.
6.5 Future research
There are a number of areas for research arising from this work. The first is a vocabulary
focussed study which uses a larger corpus. This study could encompass approach and area
control communications as well as tower. The data could be used to identify the frequency
of technical vocabulary items to determine which are high or low frequency (Coxhead, 2017)
and language required to achieve understanding of 98% of spoken interactions (Nation,
2016). The Aviation Radiotelephony Word and Number List could be extended through such
a study. A further corpus research project would be to identify the grammar of
radiotelephony as has been done in Portuguese (Silva & Tosquil Lucks, 2020).
A useful study would be to examine the specialist aviation field of Human Factors Threat
and Error Management (TEM). TEM identifies situations which are a potential threat to
safety such as a pilot who reads back correctly, but then proceeds to do something else
(ICAO, 2005). These areas are likely to require problem-solving and use more plain language.
Such a study would help identify language training needs for controllers.
Research on unusual situations and emergencies which examines the use of technical
vocabulary would be useful. A survey and interviews with controllers and pilots about
beliefs around using standard phraseology would be useful to determine the veracity of the
Model of Controller Beliefs and Language Outcomes, especially if it were coupled with
language analysis to identify technical vocabulary coverage by individuals.
It would be useful to work with air traffic control instructors to develop a radiotelephony
language training course and test for ab initio controllers. The course could be used to test
how well teaching the language separately reduces the cognitive learning load in the
simulator (Drayton & Kelly, 2019) and results in better training outcomes. Finally, a test of
radiotelephony language could be developed and trialled for use with licensed controllers.
78
6.6 Concluding remarks
This study is a response to the learning needs of ab initio air traffic control students who
would benefit from language training alongside their simulator training. Learning to manage
aircraft is a difficult task. Learning a new language at the same time makes it more difficult.
The insights gained from this research have afforded me a better understanding of the
technical vocabulary required and the areas where students might struggle. This research
has given me an insight into why there are language differences in the workplace and an
idea of how training can help minimise this divergence and reduce miscommunication.
Conversely, the investigation also highlights how training can perpetuate divergent language
use in the workplace. From a personal perspective, this research has been insightful and
invaluable.
79
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Appendices
Appendix A
Investigating language used by air traffic controllers in emergencies
A.1 Information sheet for participants
You are invited to take part in this research. Please read this information before deciding whether or not to take part. If you decide to participate, thank you. If you decide not to participate, thank you for considering this request.
Who am I?
My name is Jenny Drayton and I am a Master’s student in Applied Linguistics at Victoria University of Wellington. This research project is work towards my thesis.
What is the aim of the project?
This project is to examine the language used by air traffic controllers in emergency training in the simulator to establish training needs in the UAE. Your participation will support this research by providing examples of language used by an air traffic controller to deal with an emergency. This information will be used to develop training material for ab initio controllers. This research has been approved by the Victoria University of Wellington Human Ethics Committee HEC ID 0000027733.
How can you help?
You have been invited to participate because you are involved in emergency continuation training at GAL ANS Training Centre in Al Ain. If you agree to take part, I will record your training session with your permission and write it up later. Only those parts of the recording related to the research will be transcribed.
You are also invited to take part in an interview about your experience as an air traffic controller in the UAE, your thoughts about language use in emergencies, and about language training. The interview will take about twenty minutes. I will audio record the interview with your permission and write it up later. You can choose not to answer any question or stop the interview at any time, without giving a reason. You can withdraw from the study by contacting me at any time before 30th September, 2019. If you withdraw, the information you provided will be destroyed or returned to you.
The recordings will be used for this research. They will not be used to make a judgement about the language you use or to decide how well you dealt with the emergencies.
What will happen to the information you give?
Only my supervisor and I will read the notes or transcript of the interview. The interview transcripts, summaries and any recordings will be kept securely and destroyed on 30 August, 2024.
87
What will the project produce?
The information from my research will be used in my Master’s dissertation and/or academic
publications and conferences.
If you accept this invitation, what are your rights as a research participant?
You do not have to accept this invitation if you don’t want to. If you do decide to participate,
you have the right to:
• choose not to answer any question;
• ask for the recorder to be turned off at any time during the interview;
• withdraw from the study before 30 November, 2019;
• ask any questions about the study at any time;
• receive a copy of your training session transcript (only parts relevant to the research
will be transcribed) which you can read over and comment on;
• receive a copy of your interview recording;
• receive a copy of your interview transcript which you can read over and comment on;
• be able to read any reports of this research by emailing the researcher to request a
copy.
If you have any questions or problems, who can you contact? If you have any questions, either now or in the future, please feel free to contact either me or my supervisor:
Student: Name: Jenny Drayton University email address: [email protected]
Supervisor: Name: Dr Averil Coxhead Role: Associate Professor School: Linguistics and Applied Language Studies Phone: +64 4 4635625 [email protected]
Human Ethics Committee information
If you have any concerns about the ethical conduct of the research you may contact the
Victoria University HEC Convenor: Dr Judith Loveridge. Email [email protected] or telephone
+64-4-463 6028.
88
Investigating language used by air traffic controllers in emergencies A.2 Consent to record training session and interview
This consent form will be held for five years until 30 August, 2024.
Researcher: Jenny Drayton, School of Linguistics and Applied Language Studies, Victoria University of Wellington.
• I have read the Information Sheet and the project has been explained to me. My questions have been answered to my satisfaction. I understand that I can ask further questions at any time.
• I agree to:
an audio recording being made of my emergency continuation training session
take part in an audio recorded interview.
I understand that:
• I may withdraw from this study at any point before 30 September, 2019, and any information that I have provided will be returned to me or destroyed.
• The identifiable information I have provided will be destroyed on or before 28 February, 2020.
• Any information I provide will be kept confidential to the researcher, the supervisor and the transcriber.
• I understand that the findings may be used for a Masters dissertation and/or academic publications and/or presented to conferences.
• I understand that any observation notes and the recordings will be kept confidential to the researcher, the supervisor and the transcriber.
• My name will not be used in reports and utmost care will be taken not to disclose any information that would identify me.
• I will receive a copy of the transcript of my interview which I can read and comment on.
• I would like a copy of the recording of my interview Yes No • I would like a copy of the final transcript of my interview Yes No • I would like to receive a summary of the thesis (1 to 2 pages) Yes No
Signature of participant: ________________________________
Name of participant: ________________________________
Date: ______________
Contact details: ________________________________
89
Investigating language used by air traffic controllers in emergencies
A.3 Information sheet for GAL ANS training centre
This is a request for permission to conduct research at GAL ANS training centre.
Who am I?
My name is Jennifer Drayton, and as you know, I am a course developer at GAL ANS training centre. I am also a Master’s student in Applied Linguistics at Victoria University of Wellington. This research project is work towards my MA thesis.
What is the aim of the project?
The aim of this project is to examine the language used by air traffic controllers in emergency situations in the simulator to establish training needs in the UAE. The recordings of 20 trainees will provide examples of language used by an air traffic controller when dealing with an emergency. This information will be used to develop training material for ab initio controllers. This research has been approved by the Victoria University of Wellington Human Ethics Committee HEC ID 0000027733.
How can you help?
As you know, emergency continuation training is conducted with air traffic controllers at GAL ANS Training Centre in Al Ain. I would like to record training sessions of air traffic controllers who agree to be recorded. I would also like to conduct 20 minute interviews with ten of the participants. The interviews will be done at the training centre and I will transcribe the training sessions and interviews. To do this, I need your permission to carry out this research at the training centre.
What will happen to the information the air traffic controllers give?
Only my supervisor, Associate Professor Averil Coxhead (Victoria University of Wellington) and I will read the transcripts of the recordings and interviews. The interview transcripts, summaries and any recordings will be kept securely and destroyed on 30 August, 2024.
What will the project produce?
The information from my research will be used in my Master’s dissertation and/or academic
publications and conferences. It may also be used to inform training courses and materials
design at the training centre.
90
If you have any questions or problems, who can you contact? If you have any questions, either now or in the future, please feel free to contact either me or my supervisor:
Student: Name: Jenny Drayton University email address: [email protected]
Supervisor: Name: Dr Averil Coxhead Role: Associate Professor School: Linguistics and Applied Language Studies Phone: +64 4 4635625 [email protected]
Human Ethics Committee information
If you have any concerns about the ethical conduct of the research you may contact the
Victoria University HEC Convenor: Dr Judith Loveridge. Email [email protected] or telephone
+64-4-463 6028.
91
Investigating language used by air traffic controllers in emergencies
A.4 Consent to record training sessions and interview trainees at GAL ANS training centre
This consent form will be held for five years.
Researcher: Jenny Drayton, School of Linguistics and Applied Language Studies, Victoria University of Wellington.
I have read the Information Sheet and the project has been explained to me. My questions have been answered to my satisfaction. I understand that I can ask further questions at any time. I understand that:
• Data collection will take place between the 23rd of June and the 31st of October, 2019 • Training centre equipment will be used to record sessions • Participants may withdraw from this study at any point before the interview and any
information they have provided will be returned to them or destroyed • The identifiable material participants provide will be returned to them or destroyed on
28 February, 2020 • Any information provided by participants will be kept confidential between the
researcher and the supervisor • The results will be used for an MA thesis, academic publications and presented to
conferences
I agree that:
• the researcher can approach trainees at the GAL ANS Training Centre to record emergency training sessions and interview trainees
• GAL ANS training Centre can be identified in reports on this research • I have the authority to agree to this on behalf of the organisation.
• I would like to receive a summary of the thesis (1 to 2 pages) Yes No
Signature of Manager: ________________________________
Name of Manager: ________________________________
Date: ______________
Contact details: ________________________________
92
Investigating language used by air traffic controllers in emergencies A.5 Protocol for recruitment of research participants
Thank you for agreeing to assist me in recruiting participants for my master’s research.
This is an outline for approaching possible research participants.
Eligibility
Anybody who is at the training centre to do Emergency Continuation Training (ECT) is eligible to participate.
Recruitment
1. Explain that you are speaking to them on behalf of your colleague who is conducting research for a master’s degree from Victoria University in New Zealand. The research is about the language that air traffic controllers use in emergencies. Explain that participation is voluntary and if they would prefer not to be involved, that is no problem (if they indicate at this point that they do not want to participate, please thank them for their time).
2. Explain that any information gathered will be confidential and only the researcher and supervisor will see it. It will not be shared with GAL ANS staff members or management. It will not be used to judge their performance in the training session or their English language ability, but will be used for research purposes only.
3. If they are interested, provide the information sheet. If they are not interested, thank them for their time.
4. Once they have read the sheet, let them indicate if they would like to be involved or not or if they have further questions.
5. Remind them that participation is voluntary and answer any questions they have. If they indicate that they would prefer not to participate, please thank them for their time.
6. If they are willing to participate, please make sure they complete all sections of the form. If they do not want to be interviewed, they should tick only the first box which agrees to their training session being recorded. They may tick either or both boxes.
7. If they are not willing to participate, please thank them for their time.
Thank you
93
The following script may be used:
“Good morning / afternoon”
“I am approaching you on behalf of my colleague Jenny Drayton who is conducting research for a master’s degree from Victoria University in New Zealand. The research is about the language that air traffic controllers use in emergencies. Participation is voluntary and if you would prefer not to be involved, that is no problem” (if they indicate at this point that they do not want to participate, please thank them for their time).
“Any information gathered will be confidential and only Jenny and her research supervisor will see it. It will not be shared with GAL ANS staff members or management. It will not be used to judge your performance in the training session or your English language ability.”
If they are interested, provide the information sheet. If they are not interested, thank them for their time.
Once they have read the sheet, let them indicate if they would like to be involved or not or if they have further questions.
“As I said before, participation is voluntary. Do you have any questions?”
Answer any questions they have. If they indicate that they would prefer not to participate, please thank them for their time.
If they are willing to participate, please make sure they complete all sections of the consent form. If they do not want to be interviewed, they should tick only the first box which agrees to their training session being recorded. They may tick the first box or both boxes.
“Could you please complete this consent form which gives permission for the training session to be recorded. Also, if you are happy to be interviewed afterwards, please tick both boxes. Thank you very much for your participation.”
If they are not willing to participate, please thank them for their time.
94
Appendix B Interview questions
Thank you for agreeing to take part in this interview. It will take about 20 minutes. I’ll record
this interview, but remember you can ask me to turn off the recorder at any time. Let’s start
by talking about your language background.
1. What languages do you speak and how often do you use them?
Now I’d like to ask about your work experience.
2. How many years have you worked as an air traffic controller? 3. How many years have you worked in the UAE? 4. Where have you worked before? 5. You speak to pilots every day in your job. How does this part of your job compare to
when you speak to pilots in the simulator?
I’d like to ask you about your opinions on language training for air traffic controllers.
6. Would it help trainee air traffic controllers to learn phraseology as a separate subject (outside of the simulator)? Why/Why not?
7. Did you receive training (outside the simulator) in phraseology or English language when you trained to be an air traffic controller? Was it helpful?
8. Would you say that the language used on the radio by native English speakers and non-native English speakers is the same or different? (if different) In what ways?
9. Do you think it would be useful to give communication or language training to all air traffic controllers? Why/Why not?
10. Would language training help in emergency situations? What kinds of language training would you suggest?
95
Appendix C Tags for identification of technical vocabulary
Table C.1
Proper nouns
Tag Item representation in Doc 4444 and definition Replaced in written corpus (examples)
Identification
Callsigns Callsigns identify who is speaking and who is spoken to in an air traffic control conversation.
(UNCALLSIGN) (unit call sign) – name of the location of air traffic control unit
providing air traffic control (ICAO, 2016a) e.g. Heathrow. It is
followed by the type of air traffic control service being provided
(ICAO, 2016a) e.g. Heathrow tower or Heathrow approach.
Georgetown (tower), Alexander (approach),
Georgetown (ground)
(VECALLSIGN) Vehicle callsigns – not identified in Doc 4444, but appear in
ICAO (2007) and GCAA (2018).
Trucker 5, Worker 21
Aircraft
(CONAME) (company name) – Ownership of an aircraft Fastair
(ACTYPE) (aircraft type) Boeing 737, Boeing 747, Boeing 767, Boeing
777, C172, Cherokee, Airbus A320, Learjet,
Seneca
96
Destination, place or navigation point
(DESPLACE) (place) - Places which are part of a clearance, position report or
emergency report and can be found on an aeronautical chart
(Estival, 2016)
Kennington, Ghantoot, Jebel Ali Palms,
Sharjah, Sharjah University
Departure or Route
(SPROUTE) ROUTE (name, number or code) Route Echo
Note: The following proper noun tags were included in Table 3.4 and have not been repeated here: (ACCALLSIGN), (AERODEST), (SIGPOINT) and
(STANDARDDEP).
97
Table C.2
Number tags
Tag Item representation in Doc 4444 and definition Replaced in corpus (examples)
3 to 5-digit numbers – Altitude
(ALTNUMBER) (number) preceded by the word ALTITUDE 800, 600, 10 000, 7 000 followed by FEET
4-digit numbers
QNH, QFE or altitude followed by a number
(QNUMBER) QNH or QFE (number) air pressure required for accurate height
or altitude readings (ICAO, 2016a).
1003, 1012, 1013, 1022, 1009, 1010, 1019,
1008, 1001, 1003, 1014, 1018
24-hour time
(TIMEHOUR) TIME (number) MINUTES; TIME (time); (time) 0611, 1732, 0715 and a half
3-digit numbers
Wind direction
(WINUMBER) (number) – in the phrase, WIND (number) DEGREES 290, 260, 270, 250, 080, 370, 190, 360, 260,
250, 180, 340, 350, 070
Heading
(HDGNUMBER) HEADING (three digits) - Headings are measured in degrees and
usually preceded by the word heading.
090, 270, 190, 160, 360 and 280
98
QDM
(HDGNUMBER) QDM precedes a magnetic heading Not listed in Doc 4444, but included as QDM in
ICAO (2007) and GCAA (2018)
2-digit numbers
Runway number
(RWYDES) (number) in the phrase, RUNWAY (number) – runway direction
is given as a 2-digit number
12, 24, 30, 14, 06, 09, 31, 27, 25, 02, 20, 16, 17,
32, xx
Time in minutes
(TIMEMIN) (number) or (time) in the following phrases: TIME (number)
MINUTES; TIME (time); (time)
47, 35, 49, 27, two three and a half
1 or 2-digit numbers
Wind Speed
(WISPEED) (number) in the phrase: WIND (number) knots, and gives the
speed of the wind in knots
4, 5, 7, 8, 10, 18, 20, 22, 25
Temperature
(TENUMBER) (number) in the phrase: TEMPERATURE [MINUS] (number) – air
temperature
25, 7 and minus 2
Dewpoint temperature
(DPNUMBER) (number) in the phrase: DEWPOINT [MINUS] (number), which
can, but does not always, follow temperature.
minus 3
99
Single digit numbers
Readability Scale
(READNUMBER) Not listed in Doc 4444, but included in ICAO (2007) and GCAA
(2018) - Identifies how well the listener can hear the speaker
from unreadable 1 through to 5
three and five
Queue position
(POSQUEUE) NUMBER in the phrase: NUMBER ... FOLLOW (aircraft type and
position) - Aircraft are sometimes given a position in a queue as
number 1, 2 to come in to land for example
1, 2
Stand, hangar, gate, helipad
(NNUMBER) (number) in e.g. STAND (number) 37, 17, 24
Taxiway or Runway Intersection
(NNUMBER) - where a
number is included
(identification of taxiway); (taxiway); RUNWAY (or TAXIWAY)
(number): Intersections or taxiways usually include an aviation
alphabet letter and sometimes include a number
Radio Frequency
(NUMFREQ) (frequency) The word FREQUENCY is also used in the corpus 129.1
100
Other
POB (Persons on Board)
(NNUMBER) Not listed in Doc 4444, but included in ICAO (2007) and GCAA
(2018).
Horizontal Distance
(DISTNUMBER) (distance) (units) Visibility 8 and 20 km; distance from the end of
the runway 3, 4, 5,6, 10 and 15 miles;
distances along the runway 32, 600, 650, 700
and 1000 metres; snow on runway edge 30
cm.
Note: The following number tags were included in Table 3.4 and are not repeated here: (FLNUMBER), (SSRcode).
101
Appendix D Aviation Radiotelephony Technical Word and Number List
Table D.1
Aviation Word and Number List: Types appearing 10 or more times in list
TYPE ICAO/GCAA Ghaf Aero Sandy Aero FREQ
26 DEGREES 31 0 0 31
27 DISTNUMBER
(horizontal or vertical
distance)
29 0 0 29
28 RIGHT 27 1 0 28
29 VACATED 27 0 0 27
30 TRAFFIC 24 2 0 26
31 WILCO 19 1 5 25
32 STAND 24 0 1 25
33 DOWNWIND 25 0 0 25
34 NUMBER 19 5 0 24
35 TAXI 23 1 0 24
36 FINAL 22 0 1 23
37 NUMFREQ (radio
frequency)
21 1 0 22
38 LANDING 18 3 0 21
39 AIRCRAFT 3 4 13 20
40 SIGPOINT (significant
point)
20 0 0 20
41 FIRE 2 7 10 19
42 PROCEED 15 0 4 19
43 LEFT 17 1 0 18
44 CROSS 16 0 1 17
45 COPY 1 12 3 16
46 COPIED 6 3 6 15
47 READY 11 3 1 15
102
48 BELOW 15 0 0 15
49 MILES 15 0 0 15
50 STARTUP 15 0 0 15
51 RWYDES (runway
number)
1 13 0 14
52 BASE 8 5 1 14
53 TIMEMIN 12 2 0 14
54 STOP 11 3 0 14
55 FOLLOW 9 1 3 13
56 JOIN 12 0 1 13
57 APPROVED 13 0 0 13
58 DEPARTURE 13 0 0 13
59 TEMPERATURE 4 8 0 12
60 STANDBY 7 5 0 12
61 TOW 8 0 4 12
62 PANPAN 9 3 0 12
63 BEHIND 11 0 1 12
64 DUE 12 0 0 12
65 TAKEOFF 12 0 0 12
66 NEGATIVE 2 9 0 11
67 POB 2 9 0 11
68 TENUMBER
(temperature number)
3 8 0 11
69 VACATE 10 1 0 11
70 CONTINUE 11 0 0 11
71 GATE 11 0 0 11
72 HDGNUMBER
(heading number)
11 0 0 11
73 IMMEDIATELY 11 0 0 11
74 INFORMATION 11 0 0 11
75 CONFIRM 0 10 0 10
103
76 DESPLACE (designated
place)
8 2 0 10
77 POSITION 9 0 1 10
78 HEADING 10 0 0 10
79 TURN 10 0 0 10
104
Table D.2
Types appearing more than three times in more than one corpus
TYPE ICAO/GCAA Ghaf Aero Sandy Aero FREQ
AMBULANCE 1 7 1 9
CROSSING 8 0 1 9
EMERGENCY 3 3 3 9
STOPPING 6 3 0 9
AFFIRM 2 2 4 8
HOLD 6 0 2 8
ENGINE 6 0 1 7
MAKE 6 0 1 7
AHEAD 4 0 2 6
EXPECT 5 0 1 6
TIMEHOUR 4 0 2 6
VACATING 5 1 0 6
ALTITUDE 4 1 0 5
CALLSIGN 3 2 0 5
CHECK 0 5 0 5
PASSING 4 0 1 5
RETURN 4 1 0 5
UP 1 0 4 5
ATTENTION 1 3 0 4
CALL 3 0 1 4
DOWN 0 1 3 4
ENTER 3 1 0 4
HELIPAD 0 1 3 4
WAITING 1 2 1 4
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Table D.3
Types appearing > 4 times in written corpus
TYPE ICAO/GCAA
APRON 9
CAUTION 9
CONTACT 9
IMMEDIATE 9
LINEUP 9
METRES 9
NORTH 8
AIRBORNE 7
CANCEL 7
CLEARANCE 7
MAINTENANCE 7
VFR 7
APPROACH 6
BACKTRACK 6
CLEARED 6
HANGAR 6
PUSHBACK 6
RIGHTHAND 6
STOPBAR 6
SSRCODE 6
AERODEST 5
106
Table D.4
Multiword Units: Aircraft in the air
TYPE ICAO/GCAA Ghaf Aero Sandy Aero FREQ
(cleared for) LOW APPROACH 3 3 0 6
CONTINUE APPROACH 0 3 0 3
((cleared (for)) TOUCH AND GO
4 9 0 13
ON THE GO 0 5 0 5
GO AROUND 2 3 0 5
GOING AROUND 4 0 0 4
REQUESTING RIGHT CLOSE 0 4 0 4
RIGHT CLOSE APPROVED 0 5 0 5
REPORT RIGHT BASE 0 5 0 5
AT NUMBER 0 6 0 6
GEAR DOWN 0 3 1 4
APPEAR DOWN 4 0 0 4
APPEARS UP 4 0 0 4
Table D.5
Ground, aircraft and vehicles
TYPE ICAO/GCAA Ghaf Aero Sandy Aero FREQ
VIA TAXIWAY 0 1 4 5
ENTERING RUNWAY 0 0 4 4
107
Table D.6
Ground, Aircraft only
TYPE ICAO/GCAA Ghaf Aero Sandy Aero FREQ
LINEUP AND WAIT 3 1 0 4
LINING UP 3 1 0 4
Table D.7
Ground, vehicles only
TYPE ICAO/GCAA Ghaf Aero Sandy Aero FREQ
PROCEEDING (to) 4 6 4 14
PROCEED (on (onto)) THE RUNWAY
0 1 4 5
ON FREQUENCY 0 6 3 9
GO AHEAD 0 6 1 7
STANDBY POSITION 0 3 4 7
Table D.8
Other
TYPE ICAO/GCAA Ghaf Aero Sandy Aero FREQ
(I) SAY AGAIN 7 5 0 12
BEHIND (the) (aircraft) 0 2 2 4
STANDING BY 0 4 2 6
BE ADVISED 0 2 5 7
GOOD COPY 0 2 4 6
WIND CALM 0 0 3 3
CLEARED TO 2 1 0 3
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Table D.9
Emergency subsidiary phraseology, Ghaf Aerodrome
TYPE Ghaf Aero
FULL EMERGENCY 5
NATURE OF EMERGENCY 4
BASE OPERATION 3
MAIN FIRE 3
THIS IS THE TOWER 3
BRAKE FAILURE 6
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